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class="DesignSystem"><div class="onsite-ping" id="onsite-ping"></div></div><div class="profile-user-info DesignSystem"><div class="social-profile-container"><div class="left-panel-container"><div class="user-info-component-wrapper"><div class="user-summary-cta-container"><div class="user-summary-container"><div class="social-profile-avatar-container"><img class="profile-avatar u-positionAbsolute" alt="Thomas Schmickl" border="0" onerror="if (this.src != '//a.academia-assets.com/images/s200_no_pic.png') this.src = '//a.academia-assets.com/images/s200_no_pic.png';" width="200" height="200" src="https://0.academia-photos.com/32562090/59958077/48211262/s200_thomas.schmickl.jpeg" /></div><div class="title-container"><h1 class="ds2-5-heading-sans-serif-sm">Thomas Schmickl</h1><div class="affiliations-container fake-truncate js-profile-affiliations"><div><a class="u-tcGrayDarker" href="https://kfunigraz.academia.edu/">Karl-Franzens-University of Graz</a>, <a class="u-tcGrayDarker" href="https://kfunigraz.academia.edu/Departments/Institute_of_Biology/Documents">Institute of Biology</a>, <span class="u-tcGrayDarker">Faculty Member</span></div></div></div></div><div class="sidebar-cta-container"><button class="ds2-5-button hidden profile-cta-button grow js-profile-follow-button" data-broccoli-component="user-info.follow-button" data-click-track="profile-user-info-follow-button" data-follow-user-fname="Thomas" data-follow-user-id="32562090" data-follow-user-source="profile_button" data-has-google="false"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">add</span>Follow</button><button class="ds2-5-button hidden profile-cta-button grow js-profile-unfollow-button" data-broccoli-component="user-info.unfollow-button" data-click-track="profile-user-info-unfollow-button" data-unfollow-user-id="32562090"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">done</span>Following</button></div></div><div class="user-stats-container"><a><div class="stat-container js-profile-followers"><p class="label">Followers</p><p class="data">70</p></div></a><a><div class="stat-container js-profile-followees" data-broccoli-component="user-info.followees-count" data-click-track="profile-expand-user-info-following"><p class="label">Following</p><p class="data">14</p></div></a><a><div class="stat-container js-profile-coauthors" data-broccoli-component="user-info.coauthors-count" data-click-track="profile-expand-user-info-coauthors"><p class="label">Co-authors</p><p class="data">14</p></div></a><div class="js-mentions-count-container" style="display: none;"><a href="/ThomasSchmickl/mentions"><div class="stat-container"><p class="label">Mentions</p><p class="data"></p></div></a></div><span><div class="stat-container"><p class="label"><span class="js-profile-total-view-text">Public Views</span></p><p class="data"><span class="js-profile-view-count"></span></p></div></span></div><div class="user-bio-container"><div class="profile-bio fake-truncate js-profile-about" style="margin: 0px;">Full Professor at the University of Graz.<br /><div class="js-profile-less-about u-linkUnstyled u-tcGrayDarker u-textDecorationUnderline u-displayNone">less</div></div></div><div class="suggested-academics-container"><div class="suggested-academics--header"><p class="ds2-5-body-md-bold">Related Authors</p></div><ul class="suggested-user-card-list"><div class="suggested-user-card"><div class="suggested-user-card__avatar social-profile-avatar-container"><a href="https://asu.academia.edu/MichaelESmith"><img class="profile-avatar u-positionAbsolute" alt="Michael E Smith" border="0" onerror="if (this.src != '//a.academia-assets.com/images/s200_no_pic.png') this.src = '//a.academia-assets.com/images/s200_no_pic.png';" width="200" height="200" src="https://0.academia-photos.com/22620/7569/11258670/s200_michael_e..smith.jpg" /></a></div><div class="suggested-user-card__user-info"><a 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data-rails-context="{"inMailer":false,"i18nLocale":"en","i18nDefaultLocale":"en","href":"https://kfunigraz.academia.edu/ThomasSchmickl","location":"/ThomasSchmickl","scheme":"https","host":"kfunigraz.academia.edu","port":null,"pathname":"/ThomasSchmickl","search":null,"httpAcceptLanguage":null,"serverSide":false}"></div> <div class="js-react-on-rails-component" style="display:none" data-component-name="Pill" data-props="{"color":"gray","children":["Social Evolution"]}" data-trace="false" data-dom-id="Pill-react-component-27a564d3-65c1-45c1-b092-831d0b9afef0"></div> <div id="Pill-react-component-27a564d3-65c1-45c1-b092-831d0b9afef0"></div> </a><a data-click-track="profile-user-info-expand-research-interests" data-has-card-for-ri-list="32562090" href="https://www.academia.edu/Documents/in/Pollination"><div class="js-react-on-rails-component" style="display:none" data-component-name="Pill" data-props="{"color":"gray","children":["Pollination"]}" data-trace="false" data-dom-id="Pill-react-component-c82056af-79d6-4b7c-bfb5-6063fcda46fb"></div> <div id="Pill-react-component-c82056af-79d6-4b7c-bfb5-6063fcda46fb"></div> </a></div></div><div class="external-links-container"><ul class="profile-links new-profile js-UserInfo-social"><li class="profile-profiles js-social-profiles-container"><i class="fa fa-spin fa-spinner"></i></li></ul></div></div></div><div class="right-panel-container"><div class="user-content-wrapper"><div class="uploads-container" id="social-redesign-work-container"><div class="upload-header"><h2 class="ds2-5-heading-sans-serif-xs">Uploads</h2></div><div class="documents-container backbone-social-profile-documents" style="width: 100%;"><div class="u-taCenter"></div><div class="profile--tab_content_container js-tab-pane tab-pane active" id="all"><div class="profile--tab_heading_container js-section-heading" data-section="Papers" id="Papers"><h3 class="profile--tab_heading_container">Papers by Thomas Schmickl</h3></div><div class="js-work-strip profile--work_container" data-work-id="120181186"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/120181186/Habitat_Fragmentation"><img alt="Research paper thumbnail of Habitat Fragmentation" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/120181186/Habitat_Fragmentation">Habitat Fragmentation</a></div><div class="wp-workCard_item"><span>Springer eBooks</span><span>, 2020</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner 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href="https://www.academia.edu/120181185/PPS_3D_A_3D_Variant_of_the_Primordial_Particle_System"><img alt="Research paper thumbnail of PPS 3D: A 3D Variant of the Primordial Particle System" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/120181185/PPS_3D_A_3D_Variant_of_the_Primordial_Particle_System">PPS 3D: A 3D Variant of the Primordial Particle System</a></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="120181185"><a 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{"id":120181185,"title":"PPS 3D: A 3D Variant of the Primordial Particle System","internal_url":"https://www.academia.edu/120181185/PPS_3D_A_3D_Variant_of_the_Primordial_Particle_System","owner_id":32562090,"coauthors_can_edit":true,"owner":{"id":32562090,"first_name":"Thomas","middle_initials":null,"last_name":"Schmickl","page_name":"ThomasSchmickl","domain_name":"kfunigraz","created_at":"2015-06-26T07:05:19.783-07:00","display_name":"Thomas Schmickl","url":"https://kfunigraz.academia.edu/ThomasSchmickl"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="120181184"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/120181184/Generalization_of_the_Common_Stomach_Integral_Control_at_the_Supra_Individual_Level"><img alt="Research paper thumbnail of Generalization of the Common Stomach: Integral Control at the Supra-Individual Level" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/120181184/Generalization_of_the_Common_Stomach_Integral_Control_at_the_Supra_Individual_Level">Generalization of the Common Stomach: Integral Control at the Supra-Individual Level</a></div><div class="wp-workCard_item"><span>Springer eBooks</span><span>, 2020</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="120181184"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="120181184"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 120181184; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=120181184]").text(description); $(".js-view-count[data-work-id=120181184]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 120181184; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='120181184']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=120181184]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":120181184,"title":"Generalization of the Common Stomach: Integral Control at the Supra-Individual Level","internal_url":"https://www.academia.edu/120181184/Generalization_of_the_Common_Stomach_Integral_Control_at_the_Supra_Individual_Level","owner_id":32562090,"coauthors_can_edit":true,"owner":{"id":32562090,"first_name":"Thomas","middle_initials":null,"last_name":"Schmickl","page_name":"ThomasSchmickl","domain_name":"kfunigraz","created_at":"2015-06-26T07:05:19.783-07:00","display_name":"Thomas Schmickl","url":"https://kfunigraz.academia.edu/ThomasSchmickl"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="120181183"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/120181183/How_to_Engineer_Robotic_Organisms_and_Swarms_Bio_Inspiration_Bio_Mimicry_and_Artificial_Evolution_in_Embodied_Self_Organized_Systems"><img alt="Research paper thumbnail of How to Engineer Robotic Organisms and Swarms? - Bio-Inspiration, Bio-Mimicry, and Artificial Evolution in Embodied Self-Organized Systems" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/120181183/How_to_Engineer_Robotic_Organisms_and_Swarms_Bio_Inspiration_Bio_Mimicry_and_Artificial_Evolution_in_Embodied_Self_Organized_Systems">How to Engineer Robotic Organisms and Swarms? - Bio-Inspiration, Bio-Mimicry, and Artificial Evolution in Embodied Self-Organized Systems</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">In large-scale systems composed of autonomous embodied agents (e.g., robots), unpredictability of...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">In large-scale systems composed of autonomous embodied agents (e.g., robots), unpredictability of events, sensor noise and actuator imperfection pose significant challanges to the designers of control software. If such systems tend to selforganize, emergent phenomena prevent classical engineering approaches per se. In recent years, the Artificial Life Lab at the University of Graz has investigated a variety of methods to synthesize such control algorithms used in multi-modular robotics and in swarm robotics. These methods either translate mechanisms directly from biology to the engineering domain (bio-mimicry, bio-inspiration) or generates such controllers through artificial evolution from scratch. In this article I first discuss distributed control algorithms, which determine the collective behavior of autonomous robotic swarms. These algorithms are derived from collective behavior of honeybees and from slime mold aggregation. One of these algorithms is inspired by inter-adult food exchange in honeybees (’trophallaxis’) another one from chemical signaling in slime molds. In addition to the control of robot swarms, control paradigms for multi-modular robotic organisms are presented, which are again based on simulated fluid exchange (hormones) among compartments of robotic organisms. In both domains -swarms and organisms- the control system is self-organized and consists of many homeostatic sub-systems which adapt to each other on the individual (module) and on the collective level (organism, swarm). Additionally, I discuss the importance of distributed feedback networks, as well as the benefits and drawbacks of bio-inspiration and bio-mimicry in collective robotics.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="120181183"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="120181183"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 120181183; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=120181183]").text(description); $(".js-view-count[data-work-id=120181183]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 120181183; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='120181183']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=120181183]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":120181183,"title":"How to Engineer Robotic Organisms and Swarms? - Bio-Inspiration, Bio-Mimicry, and Artificial Evolution in Embodied Self-Organized Systems","internal_url":"https://www.academia.edu/120181183/How_to_Engineer_Robotic_Organisms_and_Swarms_Bio_Inspiration_Bio_Mimicry_and_Artificial_Evolution_in_Embodied_Self_Organized_Systems","owner_id":32562090,"coauthors_can_edit":true,"owner":{"id":32562090,"first_name":"Thomas","middle_initials":null,"last_name":"Schmickl","page_name":"ThomasSchmickl","domain_name":"kfunigraz","created_at":"2015-06-26T07:05:19.783-07:00","display_name":"Thomas Schmickl","url":"https://kfunigraz.academia.edu/ThomasSchmickl"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="120181182"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/120181182/Social_Distancing_in_Robot_Swarms_Modulating_Exploitation_and_Exploration_Without_Signal_Exchange"><img alt="Research paper thumbnail of Social Distancing in Robot Swarms: Modulating Exploitation and Exploration Without Signal Exchange" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/120181182/Social_Distancing_in_Robot_Swarms_Modulating_Exploitation_and_Exploration_Without_Signal_Exchange">Social Distancing in Robot Swarms: Modulating Exploitation and Exploration Without Signal Exchange</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The field of swarm robotics draws most of its inspiration from (eu)social animals, which leads to...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The field of swarm robotics draws most of its inspiration from (eu)social animals, which leads to the creation of bio-inspired algorithms. In this study, we show that counterintuitively - seemingly asocial behavior can also lead to successful problem solving performed by a swarm. We decided to test our new algorithm at first with real robots as a proof of concept, because this approach is of high conceptual novelty. We show that our social distancing algorithm (SocDist) performs similarly effective as a simple version of the well established bio-inspired social algorithm BEECLUST in a laboratory experiment, while avoiding some of its drawbacks. In additional agent-based computer simulation experiments we show that such an ‘asocial’ component within a swarm robotic algorithm can lead to a significant performance increase. Beside its effectiveness, the SocDist approach also leads to specific spatial distributions of the swarm robots, which may be useful for practical applications.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="120181182"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="120181182"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 120181182; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=120181182]").text(description); $(".js-view-count[data-work-id=120181182]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 120181182; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='120181182']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=120181182]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":120181182,"title":"Social Distancing in Robot Swarms: Modulating Exploitation and Exploration Without Signal Exchange","internal_url":"https://www.academia.edu/120181182/Social_Distancing_in_Robot_Swarms_Modulating_Exploitation_and_Exploration_Without_Signal_Exchange","owner_id":32562090,"coauthors_can_edit":true,"owner":{"id":32562090,"first_name":"Thomas","middle_initials":null,"last_name":"Schmickl","page_name":"ThomasSchmickl","domain_name":"kfunigraz","created_at":"2015-06-26T07:05:19.783-07:00","display_name":"Thomas Schmickl","url":"https://kfunigraz.academia.edu/ThomasSchmickl"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="120181181"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/120181181/Simple_Physical_Interactions_Yield_Social_Self_Organization_in_Honeybees"><img alt="Research paper thumbnail of Simple Physical Interactions Yield Social Self-Organization in Honeybees" class="work-thumbnail" src="https://attachments.academia-assets.com/115415418/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/120181181/Simple_Physical_Interactions_Yield_Social_Self_Organization_in_Honeybees">Simple Physical Interactions Yield Social Self-Organization in Honeybees</a></div><div class="wp-workCard_item"><span>Frontiers in Physics</span><span>, Oct 29, 2021</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Social insect colonies show all characteristics of complex adaptive systems (CAS). Their complex ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Social insect colonies show all characteristics of complex adaptive systems (CAS). Their complex behavioral patterns arise from social interactions that are based on the individuals' reactions to and interactions with environmental stimuli. We study here how social and environmental factors modulate and bias the collective thermotaxis of young honeybees. Therefore, we record their collective decision-making in a series of laboratory experiments and derived a mathematical model of the collective decisionmaking in young bees from our empirical observations. This model uses only one free parameter that combines the ultimate effects of several aspects of the microscopic individual behavioral mechanisms, such as motion behavior, sensory range, or contact detection, into one single coefficient. We call this coefficient the "social factor." Our model is capable of capturing the observed aggregation patterns from our empiric experiments with static environments and of predicting the emergent swarm-intelligent behavior of the system in dynamic environments. Besides the fundamental research aspect in studying CAS, our model enables us to predict the effects of a physical stimulus onto the macroscopic collective decision-making that affects several crucial prerequisites for efficient and effective brood production and population growth in honeybee colonies.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="bd5067527c329516eea28e5b27426aaa" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":115415418,"asset_id":120181181,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/115415418/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="120181181"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="120181181"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 120181181; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=120181181]").text(description); $(".js-view-count[data-work-id=120181181]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 120181181; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='120181181']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="120181180"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/120181180/Investigation_of_Cue_Based_Aggregation_Behaviour_in_Complex_Environments"><img alt="Research paper thumbnail of Investigation of Cue-Based Aggregation Behaviour in Complex Environments" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/120181180/Investigation_of_Cue_Based_Aggregation_Behaviour_in_Complex_Environments">Investigation of Cue-Based Aggregation Behaviour in Complex Environments</a></div><div class="wp-workCard_item"><span>Lecture Notes in Computer Science</span><span>, 2021</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Swarm robotics is mainly inspired by the collective behaviour of social animals in nature. Among ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Swarm robotics is mainly inspired by the collective behaviour of social animals in nature. Among different behaviours such as foraging and flocking performed by social animals; aggregation behaviour is often considered as the most basic and fundamental one. Aggregation behaviour has been studied in different domains for over a decade. In most of these studies, the settings are over-simplified that are quite far from reality. In this paper, we investigate cue-based aggregation behaviour using BEECLUST in a complex environment having two cues –one being the local optimum and the other being the global optimum– with an obstacle between the two cues. The robotic validation of the BEECLUST strategy in a complex environment is the main motivation of this paper. We measured the aggregation size on both cues with and without the obstacle varying the number of robots. The simulations were performed on a custom open-source simulation platform, Bee-Ground, using MONA robots. The results showed that the aggregation behaviour with BEECLUST strategy was able to overcome a certain degree of environmental complexities revealing the robustness of the method. We also verified these results using our stock-flow model.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="120181180"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="120181180"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 120181180; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=120181180]").text(description); $(".js-view-count[data-work-id=120181180]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 120181180; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='120181180']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=120181180]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":120181180,"title":"Investigation of Cue-Based Aggregation Behaviour in Complex Environments","internal_url":"https://www.academia.edu/120181180/Investigation_of_Cue_Based_Aggregation_Behaviour_in_Complex_Environments","owner_id":32562090,"coauthors_can_edit":true,"owner":{"id":32562090,"first_name":"Thomas","middle_initials":null,"last_name":"Schmickl","page_name":"ThomasSchmickl","domain_name":"kfunigraz","created_at":"2015-06-26T07:05:19.783-07:00","display_name":"Thomas Schmickl","url":"https://kfunigraz.academia.edu/ThomasSchmickl"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="120181179"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/120181179/CIMAX_collective_information_maximization_in_robotic_swarms_using_local_communication"><img alt="Research paper thumbnail of CIMAX: collective information maximization in robotic swarms using local communication" class="work-thumbnail" src="https://attachments.academia-assets.com/115415431/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/120181179/CIMAX_collective_information_maximization_in_robotic_swarms_using_local_communication">CIMAX: collective information maximization in robotic swarms using local communication</a></div><div class="wp-workCard_item"><span>Adaptive Behavior</span><span>, May 4, 2020</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Robotic swarms and mobile sensor networks are used for environmental monitoring in various domain...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Robotic swarms and mobile sensor networks are used for environmental monitoring in various domains and areas of operation. Especially in otherwise inaccessible environments, decentralized robotic swarms can be advantageous due to their high spatial resolution of measurements and resilience to failure of individuals in the swarm. However, such robotic swarms might need to be able to compensate misplacement during deployment or adapt to dynamical changes in the environment. Reaching a collective decision in a swarm with limited communication abilities without a central entity serving as decision-maker can be a challenging task. Here, we present the CIMAX algorithm for collective decision-making for maximizing the information gathered by the swarm as a whole. Agents negotiate based on their individual sensor readings and ultimately make a decision for collectively moving in a particular direction so that the swarm as a whole increases the amount of relevant measurements and thus accessible information. We use both simulation and real robotic experiments for presenting, testing, and validating our algorithm. CIMAX is designed to be used in underwater swarm robots for troubleshooting an oxygen depletion phenomenon known as ''anoxia.''</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="06db588bb2dcd2d09948912b9c719c4c" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":115415431,"asset_id":120181179,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/115415431/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="120181179"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="120181179"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 120181179; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=120181179]").text(description); $(".js-view-count[data-work-id=120181179]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 120181179; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='120181179']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "06db588bb2dcd2d09948912b9c719c4c" } } $('.js-work-strip[data-work-id=120181179]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":120181179,"title":"CIMAX: collective information maximization in robotic swarms using local communication","internal_url":"https://www.academia.edu/120181179/CIMAX_collective_information_maximization_in_robotic_swarms_using_local_communication","owner_id":32562090,"coauthors_can_edit":true,"owner":{"id":32562090,"first_name":"Thomas","middle_initials":null,"last_name":"Schmickl","page_name":"ThomasSchmickl","domain_name":"kfunigraz","created_at":"2015-06-26T07:05:19.783-07:00","display_name":"Thomas Schmickl","url":"https://kfunigraz.academia.edu/ThomasSchmickl"},"attachments":[{"id":115415431,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/115415431/thumbnails/1.jpg","file_name":"1059712320912021.pdf","download_url":"https://www.academia.edu/attachments/115415431/download_file","bulk_download_file_name":"CIMAX_collective_information_maximizatio.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/115415431/1059712320912021-libre.pdf?1716935968=\u0026response-content-disposition=attachment%3B+filename%3DCIMAX_collective_information_maximizatio.pdf\u0026Expires=1740594161\u0026Signature=gHjC4rCCkJWLH00PU2gXGhunv0uVpSTb~X3-Y0fWc6rXaOVkkn4IGpc8RR-hxNbhK7UbuUAfBhPFjE8J8IcGOG0kL30vXZPtUhJozt4EzHceMa7LyOh-h8~3D889QiE5Mq3~7uikGs6jo94ZvuYAx1fCRrmteVYhWOvRwBEcJLlKMmVMQTi5iR3Thp-kU1Mk3NWeZcunWDvO0dCM7sf7dQk9w8xO5d6nNUQKF8zdwhAROA21T7atQsJ5RGjAdM5i8ST8hYN~24I4uN417CdlRJxKWhdjK8fTzi2iink0gpFT18WPlxjBXGnfw0DSXyZBRXEKRRPlWzSTmuOtkCDrqw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="120181178"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/120181178/Confirmation_Bias_as_a_Mechanism_to_Focus_Attention_Enhances_Signal_Detection"><img alt="Research paper thumbnail of Confirmation Bias as a Mechanism to Focus Attention Enhances Signal Detection" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/120181178/Confirmation_Bias_as_a_Mechanism_to_Focus_Attention_Enhances_Signal_Detection">Confirmation Bias as a Mechanism to Focus Attention Enhances Signal Detection</a></div><div class="wp-workCard_item"><span>Journal of Artificial Societies and Social Simulation</span><span>, 2023</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="120181178"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="120181178"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 120181178; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=120181174]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":120181174,"title":"Understanding Ecosystem Stability and Resilience Through Mathematical Modeling","internal_url":"https://www.academia.edu/120181174/Understanding_Ecosystem_Stability_and_Resilience_Through_Mathematical_Modeling","owner_id":32562090,"coauthors_can_edit":true,"owner":{"id":32562090,"first_name":"Thomas","middle_initials":null,"last_name":"Schmickl","page_name":"ThomasSchmickl","domain_name":"kfunigraz","created_at":"2015-06-26T07:05:19.783-07:00","display_name":"Thomas Schmickl","url":"https://kfunigraz.academia.edu/ThomasSchmickl"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="120181173"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/120181173/Integral_feedback_control_is_at_the_core_of_task_allocation_and_resilience_of_insect_societies"><img alt="Research paper thumbnail of Integral feedback control is at the core of task allocation and resilience of insect societies" class="work-thumbnail" src="https://attachments.academia-assets.com/115415426/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/120181173/Integral_feedback_control_is_at_the_core_of_task_allocation_and_resilience_of_insect_societies">Integral feedback control is at the core of task allocation and resilience of insect societies</a></div><div class="wp-workCard_item"><span>Proceedings of the National Academy of Sciences of the United States of America</span><span>, Dec 10, 2018</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="8493a8ea7bf0edc77d90c415026d380e" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":115415426,"asset_id":120181173,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/115415426/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="120181173"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="120181173"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 120181173; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=120181173]").text(description); $(".js-view-count[data-work-id=120181173]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 120181173; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='120181173']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="120181172"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/120181172/Strong_Emergence_Arising_from_Weak_Emergence"><img alt="Research paper thumbnail of Strong Emergence Arising from Weak Emergence" class="work-thumbnail" src="https://attachments.academia-assets.com/115415417/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/120181172/Strong_Emergence_Arising_from_Weak_Emergence">Strong Emergence Arising from Weak Emergence</a></div><div class="wp-workCard_item"><span>Complexity</span><span>, Nov 25, 2022</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Predictions of emergent phenomena, appearing on the macroscopic layer of a complex system, can fa...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Predictions of emergent phenomena, appearing on the macroscopic layer of a complex system, can fail if they are made by a microscopic model. Tis study demonstrates and analyses this claim on a well-known complex system, Conway's Game of Life. Straightforward macroscopic mean-feld models are easily capable of predicting such emergent properties after they have been ftted to simulation data in an after-the-fact way. Tus, these predictions are macro-to-macro only. However, a micro-to-macro model signifcantly fails to predict correctly, as does the obvious mesoscopic modeling approach. Tis suggests that some macroscopic system properties in a complex dynamic system should be interpreted as examples of phenomena (properties) arising from "strong emergence," due to the lack of ability to build a consistent micro-to-macro model, that could explain these phenomena in a before-the-fact way. Te root cause for this inability to predict this in a micro-to-macro way is identifed as the pattern formation process, a phenomenon that is usually classifed as being of "weak emergence." Ultimately, this suggests that it may be in principle impossible to discriminate between such distinct categories of "weak" and "strong" emergence, as phenomena of both types can be part of the very same feedback loop that mainly governs the system's dynamics.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="9dd12bf4de242e7fb1bf0bf2d8cee088" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":115415417,"asset_id":120181172,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/115415417/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="120181172"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="120181172"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 120181172; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "9dd12bf4de242e7fb1bf0bf2d8cee088" } } $('.js-work-strip[data-work-id=120181172]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":120181172,"title":"Strong Emergence Arising from Weak Emergence","internal_url":"https://www.academia.edu/120181172/Strong_Emergence_Arising_from_Weak_Emergence","owner_id":32562090,"coauthors_can_edit":true,"owner":{"id":32562090,"first_name":"Thomas","middle_initials":null,"last_name":"Schmickl","page_name":"ThomasSchmickl","domain_name":"kfunigraz","created_at":"2015-06-26T07:05:19.783-07:00","display_name":"Thomas Schmickl","url":"https://kfunigraz.academia.edu/ThomasSchmickl"},"attachments":[{"id":115415417,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/115415417/thumbnails/1.jpg","file_name":"9956885.pdf","download_url":"https://www.academia.edu/attachments/115415417/download_file","bulk_download_file_name":"Strong_Emergence_Arising_from_Weak_Emerg.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/115415417/9956885-libre.pdf?1716935980=\u0026response-content-disposition=attachment%3B+filename%3DStrong_Emergence_Arising_from_Weak_Emerg.pdf\u0026Expires=1740594161\u0026Signature=XgxOdbrG-UKywAUjjo5WGRavixZBdx-eLmsPmGj5DBUVC4sy-UNAtLvsKdXMvTx7rG2tJmQ4no5SpJNSyxfRjuvU4PTnZtoKUKXyV-ECU5R0uLA2L96W1io60Ovh-f~B3BSqD5fwPqJK0WlqoZCVMWqchElD6ThTcx1av0aK1VqUWqvSADSeHp3W4l4FqI1uQOJrBBv85Oy7jO9ZT2fS4Y~dJEGq8b1S~tY6YerWZJRQq7h8N1rMeBRTERuj72xNhqz11FDj-HFmSR10xld-UbBNdonpjP324f1mbTQI6zzFe4u6E4r8gP-1~xTpUuM~ZqbfMbM~Olm4-ERQGmnCPQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="120181171"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/120181171/Forest_Fires_Fire_Management_and_the_Power_Law"><img alt="Research paper thumbnail of Forest Fires: Fire Management and the Power Law" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/120181171/Forest_Fires_Fire_Management_and_the_Power_Law">Forest Fires: Fire Management and the Power Law</a></div><div class="wp-workCard_item"><span>Springer eBooks</span><span>, 2020</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="120181171"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="120181171"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 120181171; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=120181171]").text(description); $(".js-view-count[data-work-id=120181171]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 120181171; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='120181171']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=120181171]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":120181171,"title":"Forest Fires: Fire Management and the Power Law","internal_url":"https://www.academia.edu/120181171/Forest_Fires_Fire_Management_and_the_Power_Law","owner_id":32562090,"coauthors_can_edit":true,"owner":{"id":32562090,"first_name":"Thomas","middle_initials":null,"last_name":"Schmickl","page_name":"ThomasSchmickl","domain_name":"kfunigraz","created_at":"2015-06-26T07:05:19.783-07:00","display_name":"Thomas Schmickl","url":"https://kfunigraz.academia.edu/ThomasSchmickl"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="120181170"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/120181170/Fundamentalism_in_a_social_learning_perspective_A_memetic_agent_model_of_vegetarianism_social_interaction_networks_and_food_markets"><img alt="Research paper thumbnail of Fundamentalism in a social learning perspective: A memetic agent model of vegetarianism, social interaction networks and food markets" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/120181170/Fundamentalism_in_a_social_learning_perspective_A_memetic_agent_model_of_vegetarianism_social_interaction_networks_and_food_markets">Fundamentalism in a social learning perspective: A memetic agent model of vegetarianism, social interaction networks and food markets</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Fundamentalism and extremism are behavioral traits prominently observed today, ranging from relig...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Fundamentalism and extremism are behavioral traits prominently observed today, ranging from religion and ideology to product choices and even dietary preferences. This study develops a multi-agent model depicting the exemplary case of preventing to eat meat (vegetarianism) or animal-derived products (veganism) as a set of “memes” that can evolve within a society. Behavioral traits can develop over time by means of (local) individual-based adaptation to an ultimate societal phenomenon by cultural (global) learning. The multi-agent model presented here predicts that fundamentalist strategies emerge in significant amounts only if certain extreme starting conditions of the environment (market) or of the initial population are met. When starting from non-extreme conditions, the population develops towards moderate behavioral traits and the market adapts to comfort these society-level adaptations. The underlying social network structure has a significant effect on those processes, as fundamentalism occurs only in fragmented subpopulations as longer-lasting phenomena. A very simple mechanism of social interaction is capable to capture general principles of the emergence of fundamentalist traits in societies.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="120181170"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="120181170"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 120181170; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); 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</script> <div class="js-work-strip profile--work_container" data-work-id="120181169"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/120181169/Morphogenesis_as_a_Collective_Decision_of_Agents_Competing_for_Limited_Resource_A_Plants_Approach"><img alt="Research paper thumbnail of Morphogenesis as a Collective Decision of Agents Competing for Limited Resource: A Plants Approach" class="work-thumbnail" src="https://attachments.academia-assets.com/115415425/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/120181169/Morphogenesis_as_a_Collective_Decision_of_Agents_Competing_for_Limited_Resource_A_Plants_Approach">Morphogenesis as a Collective Decision of Agents Competing for Limited Resource: A Plants Approach</a></div><div class="wp-workCard_item"><span>Lecture Notes in Computer Science</span><span>, 2018</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Competition for limited resource is a common concept in many artificial and natural collective sy...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Competition for limited resource is a common concept in many artificial and natural collective systems. In plants, the common resources-water, minerals and the products of photosynthesis-are a subject of competition for individual branches striving for growth. The competition is realized via a dynamic vascular system resulting in the dynamic morphology of the plant that is adapting to its environment. In this paper, a distributed morphogenesis algorithm inspired by the competition for limited resources in plants is described and is validated in directing the growth of a physical structure made out of braided modules. The effects of different parameters of the algorithm on the growth behavior of the structure are discussed analytically and similar effects are demonstrated in the physical system.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="45b5927ef9a1381f20a7101c16ec0b75" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":115415425,"asset_id":120181169,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/115415425/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="120181169"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="120181169"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 120181169; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="120181167"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/120181167/Vascular_Morphogenesis_Controller_A_Distributed_Controller_for_Growing_Artificial_Structures"><img alt="Research paper thumbnail of Vascular Morphogenesis Controller: A Distributed Controller for Growing Artificial Structures" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/120181167/Vascular_Morphogenesis_Controller_A_Distributed_Controller_for_Growing_Artificial_Structures">Vascular Morphogenesis Controller: A Distributed Controller for Growing Artificial Structures</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">It is a challenging task to develop morphologies of structures in response to dynamic environment...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">It is a challenging task to develop morphologies of structures in response to dynamic environmental factors and constraints. In the context of the EU-funded project flora robotica [1] we are interested in developing selforganized methods that combine local considerations and global requirements and drive the development of structures. Embryogenetic development of biological organisms and cell differentiation are studied for a long time in evolutionary developmental biology (EvoDevo) [2], [3]. Some of the mechanisms from that field are already applied to pattern formation [4] and development of body morphologies [5], [6] and controllers [7] in evolutionary robotics [8] and modular robotics [9]. In this work, vascular system and branching dynamics of plants are used as the source of inspiration for designing a novel algorithm called &quot;Vascular Morphogenesis Controller&quot; (VMC) that is applied to morphological development of modular structures. Plant vessels develop in the stems and roots. They transport water and minerals from the roots to the leaves, and sugars and photosynthates from the leaves to other parts of the plant [10]. There are evidences [11], [12] suggesting that there is a competition between different branches over the vascular growth. The branches that are in better situations (e.g., get more light) produce more photosynthates that flow back from the leaves. The higher flow rate leads to more vascular tissues in the branch and therefore more water and minerals from the roots reach the branch. More water and minerals facilitate the growth of the branch and the branch may end up in an even better situation which in turn reinforces the growth. Different branches with their different local conditions compete over production of new vessels. On the other hand, global resources (i.e., water) are limited and the vessels are subject to degradation as well. Based on the positive and negative feedback loops established by this competition and limitation, a dynamic system of vessels shape the growth of the plants.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="120181167"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="120181167"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 120181167; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); 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window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=120181186]").text(description); $(".js-view-count[data-work-id=120181186]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 120181186; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='120181186']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=120181186]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":120181186,"title":"Habitat Fragmentation","internal_url":"https://www.academia.edu/120181186/Habitat_Fragmentation","owner_id":32562090,"coauthors_can_edit":true,"owner":{"id":32562090,"first_name":"Thomas","middle_initials":null,"last_name":"Schmickl","page_name":"ThomasSchmickl","domain_name":"kfunigraz","created_at":"2015-06-26T07:05:19.783-07:00","display_name":"Thomas Schmickl","url":"https://kfunigraz.academia.edu/ThomasSchmickl"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="120181185"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/120181185/PPS_3D_A_3D_Variant_of_the_Primordial_Particle_System"><img alt="Research paper thumbnail of PPS 3D: A 3D Variant of the Primordial Particle System" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/120181185/PPS_3D_A_3D_Variant_of_the_Primordial_Particle_System">PPS 3D: A 3D Variant of the Primordial Particle System</a></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="120181185"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="120181185"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 120181185; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=120181185]").text(description); $(".js-view-count[data-work-id=120181185]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 120181185; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='120181185']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=120181185]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":120181185,"title":"PPS 3D: A 3D Variant of the Primordial Particle System","internal_url":"https://www.academia.edu/120181185/PPS_3D_A_3D_Variant_of_the_Primordial_Particle_System","owner_id":32562090,"coauthors_can_edit":true,"owner":{"id":32562090,"first_name":"Thomas","middle_initials":null,"last_name":"Schmickl","page_name":"ThomasSchmickl","domain_name":"kfunigraz","created_at":"2015-06-26T07:05:19.783-07:00","display_name":"Thomas Schmickl","url":"https://kfunigraz.academia.edu/ThomasSchmickl"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="120181184"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/120181184/Generalization_of_the_Common_Stomach_Integral_Control_at_the_Supra_Individual_Level"><img alt="Research paper thumbnail of Generalization of the Common Stomach: Integral Control at the Supra-Individual Level" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/120181184/Generalization_of_the_Common_Stomach_Integral_Control_at_the_Supra_Individual_Level">Generalization of the Common Stomach: Integral Control at the Supra-Individual Level</a></div><div class="wp-workCard_item"><span>Springer eBooks</span><span>, 2020</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="120181184"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="120181184"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 120181184; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=120181184]").text(description); $(".js-view-count[data-work-id=120181184]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 120181184; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='120181184']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=120181184]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":120181184,"title":"Generalization of the Common Stomach: Integral Control at the Supra-Individual Level","internal_url":"https://www.academia.edu/120181184/Generalization_of_the_Common_Stomach_Integral_Control_at_the_Supra_Individual_Level","owner_id":32562090,"coauthors_can_edit":true,"owner":{"id":32562090,"first_name":"Thomas","middle_initials":null,"last_name":"Schmickl","page_name":"ThomasSchmickl","domain_name":"kfunigraz","created_at":"2015-06-26T07:05:19.783-07:00","display_name":"Thomas Schmickl","url":"https://kfunigraz.academia.edu/ThomasSchmickl"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="120181183"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/120181183/How_to_Engineer_Robotic_Organisms_and_Swarms_Bio_Inspiration_Bio_Mimicry_and_Artificial_Evolution_in_Embodied_Self_Organized_Systems"><img alt="Research paper thumbnail of How to Engineer Robotic Organisms and Swarms? - Bio-Inspiration, Bio-Mimicry, and Artificial Evolution in Embodied Self-Organized Systems" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/120181183/How_to_Engineer_Robotic_Organisms_and_Swarms_Bio_Inspiration_Bio_Mimicry_and_Artificial_Evolution_in_Embodied_Self_Organized_Systems">How to Engineer Robotic Organisms and Swarms? - Bio-Inspiration, Bio-Mimicry, and Artificial Evolution in Embodied Self-Organized Systems</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">In large-scale systems composed of autonomous embodied agents (e.g., robots), unpredictability of...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">In large-scale systems composed of autonomous embodied agents (e.g., robots), unpredictability of events, sensor noise and actuator imperfection pose significant challanges to the designers of control software. If such systems tend to selforganize, emergent phenomena prevent classical engineering approaches per se. In recent years, the Artificial Life Lab at the University of Graz has investigated a variety of methods to synthesize such control algorithms used in multi-modular robotics and in swarm robotics. These methods either translate mechanisms directly from biology to the engineering domain (bio-mimicry, bio-inspiration) or generates such controllers through artificial evolution from scratch. In this article I first discuss distributed control algorithms, which determine the collective behavior of autonomous robotic swarms. These algorithms are derived from collective behavior of honeybees and from slime mold aggregation. One of these algorithms is inspired by inter-adult food exchange in honeybees (’trophallaxis’) another one from chemical signaling in slime molds. In addition to the control of robot swarms, control paradigms for multi-modular robotic organisms are presented, which are again based on simulated fluid exchange (hormones) among compartments of robotic organisms. In both domains -swarms and organisms- the control system is self-organized and consists of many homeostatic sub-systems which adapt to each other on the individual (module) and on the collective level (organism, swarm). Additionally, I discuss the importance of distributed feedback networks, as well as the benefits and drawbacks of bio-inspiration and bio-mimicry in collective robotics.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="120181183"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="120181183"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 120181183; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=120181183]").text(description); $(".js-view-count[data-work-id=120181183]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 120181183; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='120181183']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=120181183]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":120181183,"title":"How to Engineer Robotic Organisms and Swarms? - Bio-Inspiration, Bio-Mimicry, and Artificial Evolution in Embodied Self-Organized Systems","internal_url":"https://www.academia.edu/120181183/How_to_Engineer_Robotic_Organisms_and_Swarms_Bio_Inspiration_Bio_Mimicry_and_Artificial_Evolution_in_Embodied_Self_Organized_Systems","owner_id":32562090,"coauthors_can_edit":true,"owner":{"id":32562090,"first_name":"Thomas","middle_initials":null,"last_name":"Schmickl","page_name":"ThomasSchmickl","domain_name":"kfunigraz","created_at":"2015-06-26T07:05:19.783-07:00","display_name":"Thomas Schmickl","url":"https://kfunigraz.academia.edu/ThomasSchmickl"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="120181182"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/120181182/Social_Distancing_in_Robot_Swarms_Modulating_Exploitation_and_Exploration_Without_Signal_Exchange"><img alt="Research paper thumbnail of Social Distancing in Robot Swarms: Modulating Exploitation and Exploration Without Signal Exchange" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/120181182/Social_Distancing_in_Robot_Swarms_Modulating_Exploitation_and_Exploration_Without_Signal_Exchange">Social Distancing in Robot Swarms: Modulating Exploitation and Exploration Without Signal Exchange</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The field of swarm robotics draws most of its inspiration from (eu)social animals, which leads to...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The field of swarm robotics draws most of its inspiration from (eu)social animals, which leads to the creation of bio-inspired algorithms. In this study, we show that counterintuitively - seemingly asocial behavior can also lead to successful problem solving performed by a swarm. We decided to test our new algorithm at first with real robots as a proof of concept, because this approach is of high conceptual novelty. We show that our social distancing algorithm (SocDist) performs similarly effective as a simple version of the well established bio-inspired social algorithm BEECLUST in a laboratory experiment, while avoiding some of its drawbacks. In additional agent-based computer simulation experiments we show that such an ‘asocial’ component within a swarm robotic algorithm can lead to a significant performance increase. Beside its effectiveness, the SocDist approach also leads to specific spatial distributions of the swarm robots, which may be useful for practical applications.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="120181182"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="120181182"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 120181182; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=120181182]").text(description); $(".js-view-count[data-work-id=120181182]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 120181182; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='120181182']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=120181182]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":120181182,"title":"Social Distancing in Robot Swarms: Modulating Exploitation and Exploration Without Signal Exchange","internal_url":"https://www.academia.edu/120181182/Social_Distancing_in_Robot_Swarms_Modulating_Exploitation_and_Exploration_Without_Signal_Exchange","owner_id":32562090,"coauthors_can_edit":true,"owner":{"id":32562090,"first_name":"Thomas","middle_initials":null,"last_name":"Schmickl","page_name":"ThomasSchmickl","domain_name":"kfunigraz","created_at":"2015-06-26T07:05:19.783-07:00","display_name":"Thomas Schmickl","url":"https://kfunigraz.academia.edu/ThomasSchmickl"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="120181181"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/120181181/Simple_Physical_Interactions_Yield_Social_Self_Organization_in_Honeybees"><img alt="Research paper thumbnail of Simple Physical Interactions Yield Social Self-Organization in Honeybees" class="work-thumbnail" src="https://attachments.academia-assets.com/115415418/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/120181181/Simple_Physical_Interactions_Yield_Social_Self_Organization_in_Honeybees">Simple Physical Interactions Yield Social Self-Organization in Honeybees</a></div><div class="wp-workCard_item"><span>Frontiers in Physics</span><span>, Oct 29, 2021</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Social insect colonies show all characteristics of complex adaptive systems (CAS). Their complex ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Social insect colonies show all characteristics of complex adaptive systems (CAS). Their complex behavioral patterns arise from social interactions that are based on the individuals' reactions to and interactions with environmental stimuli. We study here how social and environmental factors modulate and bias the collective thermotaxis of young honeybees. Therefore, we record their collective decision-making in a series of laboratory experiments and derived a mathematical model of the collective decisionmaking in young bees from our empirical observations. This model uses only one free parameter that combines the ultimate effects of several aspects of the microscopic individual behavioral mechanisms, such as motion behavior, sensory range, or contact detection, into one single coefficient. We call this coefficient the "social factor." Our model is capable of capturing the observed aggregation patterns from our empiric experiments with static environments and of predicting the emergent swarm-intelligent behavior of the system in dynamic environments. Besides the fundamental research aspect in studying CAS, our model enables us to predict the effects of a physical stimulus onto the macroscopic collective decision-making that affects several crucial prerequisites for efficient and effective brood production and population growth in honeybee colonies.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="bd5067527c329516eea28e5b27426aaa" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":115415418,"asset_id":120181181,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/115415418/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="120181181"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="120181181"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 120181181; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=120181181]").text(description); $(".js-view-count[data-work-id=120181181]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 120181181; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='120181181']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "bd5067527c329516eea28e5b27426aaa" } } $('.js-work-strip[data-work-id=120181181]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":120181181,"title":"Simple Physical Interactions Yield Social Self-Organization in Honeybees","internal_url":"https://www.academia.edu/120181181/Simple_Physical_Interactions_Yield_Social_Self_Organization_in_Honeybees","owner_id":32562090,"coauthors_can_edit":true,"owner":{"id":32562090,"first_name":"Thomas","middle_initials":null,"last_name":"Schmickl","page_name":"ThomasSchmickl","domain_name":"kfunigraz","created_at":"2015-06-26T07:05:19.783-07:00","display_name":"Thomas Schmickl","url":"https://kfunigraz.academia.edu/ThomasSchmickl"},"attachments":[{"id":115415418,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/115415418/thumbnails/1.jpg","file_name":"pdf.pdf","download_url":"https://www.academia.edu/attachments/115415418/download_file","bulk_download_file_name":"Simple_Physical_Interactions_Yield_Socia.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/115415418/pdf-libre.pdf?1716935979=\u0026response-content-disposition=attachment%3B+filename%3DSimple_Physical_Interactions_Yield_Socia.pdf\u0026Expires=1739717271\u0026Signature=f~-oWZ1LGU2qYsBvsKM3F9KtSaivYIoNMeCE9KK7~YuIupPRNnayA5IdLqT4JlGdg2bPbGtkkcK6004jyXCgpEzN6C1HrucRAvthtgDGFTeVroOFEnvN1QUffnWC3NmyZf-EaV2ws7majkvmQOTIKziQsGMdBgJP0Y0TgR3DJEHuqnpBWTE1KqzjCAwoU29qLKy4JUNIluVi~~KhKsth0iQM4-4rtYcZCwpRQzBWmD0KIOZgss9yf2OdG8ZRK4HVrwCZ2aUtiA1B~QDHYaPszJ4A~aUFC-L8LmjErmWhR5Hnopj0BWMhCbCjUIMv2-tRPXpgxDU4Y7jmMSIL13mJTw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"},{"id":115415419,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/115415419/thumbnails/1.jpg","file_name":"pdf.pdf","download_url":"https://www.academia.edu/attachments/115415419/download_file","bulk_download_file_name":"Simple_Physical_Interactions_Yield_Socia.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/115415419/pdf-libre.pdf?1716935972=\u0026response-content-disposition=attachment%3B+filename%3DSimple_Physical_Interactions_Yield_Socia.pdf\u0026Expires=1739717271\u0026Signature=Prlk~HBue37OaszRD6aw6a0DaLLYH05OeA~lxTu8RdXOE-xxUeaUReR6oJ7BnvjQNgNqLP~69I7leILGR8D6P~wINWJFsf3qt8dKCwNMB43WGC1bTatfBy105cRJ~wMbir5-hLXtV4nzOXcwrTI8q1coZtDK61DqEL~1wdnUbPFPdysJxi7XjMX43IqF~nijUwyuC2bYxqZ5knRXaW-wqjP6BtDD~xixRg4wyAhTDyfEUrj6UNhw1ePlVfO3jx~yd9FKKnOd4BBmcKp8OtrW15cMGmmJ0d92lB2P7eSVi8S4Tk2ib0SLkXqIhYGRJnU4IvmmAEMjTrwgY1pLoxyY6w__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="120181180"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/120181180/Investigation_of_Cue_Based_Aggregation_Behaviour_in_Complex_Environments"><img alt="Research paper thumbnail of Investigation of Cue-Based Aggregation Behaviour in Complex Environments" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/120181180/Investigation_of_Cue_Based_Aggregation_Behaviour_in_Complex_Environments">Investigation of Cue-Based Aggregation Behaviour in Complex Environments</a></div><div class="wp-workCard_item"><span>Lecture Notes in Computer Science</span><span>, 2021</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Swarm robotics is mainly inspired by the collective behaviour of social animals in nature. Among ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Swarm robotics is mainly inspired by the collective behaviour of social animals in nature. Among different behaviours such as foraging and flocking performed by social animals; aggregation behaviour is often considered as the most basic and fundamental one. Aggregation behaviour has been studied in different domains for over a decade. In most of these studies, the settings are over-simplified that are quite far from reality. In this paper, we investigate cue-based aggregation behaviour using BEECLUST in a complex environment having two cues –one being the local optimum and the other being the global optimum– with an obstacle between the two cues. The robotic validation of the BEECLUST strategy in a complex environment is the main motivation of this paper. We measured the aggregation size on both cues with and without the obstacle varying the number of robots. The simulations were performed on a custom open-source simulation platform, Bee-Ground, using MONA robots. The results showed that the aggregation behaviour with BEECLUST strategy was able to overcome a certain degree of environmental complexities revealing the robustness of the method. We also verified these results using our stock-flow model.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="120181180"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="120181180"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 120181180; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=120181180]").text(description); $(".js-view-count[data-work-id=120181180]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 120181180; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='120181180']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=120181180]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":120181180,"title":"Investigation of Cue-Based Aggregation Behaviour in Complex Environments","internal_url":"https://www.academia.edu/120181180/Investigation_of_Cue_Based_Aggregation_Behaviour_in_Complex_Environments","owner_id":32562090,"coauthors_can_edit":true,"owner":{"id":32562090,"first_name":"Thomas","middle_initials":null,"last_name":"Schmickl","page_name":"ThomasSchmickl","domain_name":"kfunigraz","created_at":"2015-06-26T07:05:19.783-07:00","display_name":"Thomas Schmickl","url":"https://kfunigraz.academia.edu/ThomasSchmickl"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="120181179"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/120181179/CIMAX_collective_information_maximization_in_robotic_swarms_using_local_communication"><img alt="Research paper thumbnail of CIMAX: collective information maximization in robotic swarms using local communication" class="work-thumbnail" src="https://attachments.academia-assets.com/115415431/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/120181179/CIMAX_collective_information_maximization_in_robotic_swarms_using_local_communication">CIMAX: collective information maximization in robotic swarms using local communication</a></div><div class="wp-workCard_item"><span>Adaptive Behavior</span><span>, May 4, 2020</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Robotic swarms and mobile sensor networks are used for environmental monitoring in various domain...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Robotic swarms and mobile sensor networks are used for environmental monitoring in various domains and areas of operation. Especially in otherwise inaccessible environments, decentralized robotic swarms can be advantageous due to their high spatial resolution of measurements and resilience to failure of individuals in the swarm. However, such robotic swarms might need to be able to compensate misplacement during deployment or adapt to dynamical changes in the environment. Reaching a collective decision in a swarm with limited communication abilities without a central entity serving as decision-maker can be a challenging task. Here, we present the CIMAX algorithm for collective decision-making for maximizing the information gathered by the swarm as a whole. Agents negotiate based on their individual sensor readings and ultimately make a decision for collectively moving in a particular direction so that the swarm as a whole increases the amount of relevant measurements and thus accessible information. We use both simulation and real robotic experiments for presenting, testing, and validating our algorithm. 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Kaplan u.a.: »The Prehistoric and Preindustrial Deforestation of Europe«. 4 Vgl. Covington u...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Vgl. Kaplan u.a.: »The Prehistoric and Preindustrial Deforestation of Europe«. 4 Vgl. Covington u.a.: »Historical and Anticipated Changes in Forest Ecosystems of the Inland West of the United States«. 5 Vgl. Shi u.a.: »Preventing Smog Crises in China and Globally«.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="728f5f4d589268e91ae40ef3d7b5b969" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":115415420,"asset_id":120181177,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/115415420/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="120181177"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="120181177"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 120181177; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="120181172"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/120181172/Strong_Emergence_Arising_from_Weak_Emergence"><img alt="Research paper thumbnail of Strong Emergence Arising from Weak Emergence" class="work-thumbnail" src="https://attachments.academia-assets.com/115415417/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/120181172/Strong_Emergence_Arising_from_Weak_Emergence">Strong Emergence Arising from Weak Emergence</a></div><div class="wp-workCard_item"><span>Complexity</span><span>, Nov 25, 2022</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Predictions of emergent phenomena, appearing on the macroscopic layer of a complex system, can fa...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Predictions of emergent phenomena, appearing on the macroscopic layer of a complex system, can fail if they are made by a microscopic model. Tis study demonstrates and analyses this claim on a well-known complex system, Conway's Game of Life. Straightforward macroscopic mean-feld models are easily capable of predicting such emergent properties after they have been ftted to simulation data in an after-the-fact way. Tus, these predictions are macro-to-macro only. However, a micro-to-macro model signifcantly fails to predict correctly, as does the obvious mesoscopic modeling approach. Tis suggests that some macroscopic system properties in a complex dynamic system should be interpreted as examples of phenomena (properties) arising from "strong emergence," due to the lack of ability to build a consistent micro-to-macro model, that could explain these phenomena in a before-the-fact way. Te root cause for this inability to predict this in a micro-to-macro way is identifed as the pattern formation process, a phenomenon that is usually classifed as being of "weak emergence." Ultimately, this suggests that it may be in principle impossible to discriminate between such distinct categories of "weak" and "strong" emergence, as phenomena of both types can be part of the very same feedback loop that mainly governs the system's dynamics.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="9dd12bf4de242e7fb1bf0bf2d8cee088" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":115415417,"asset_id":120181172,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/115415417/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="120181172"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="120181172"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 120181172; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "9dd12bf4de242e7fb1bf0bf2d8cee088" } } $('.js-work-strip[data-work-id=120181172]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":120181172,"title":"Strong Emergence Arising from Weak Emergence","internal_url":"https://www.academia.edu/120181172/Strong_Emergence_Arising_from_Weak_Emergence","owner_id":32562090,"coauthors_can_edit":true,"owner":{"id":32562090,"first_name":"Thomas","middle_initials":null,"last_name":"Schmickl","page_name":"ThomasSchmickl","domain_name":"kfunigraz","created_at":"2015-06-26T07:05:19.783-07:00","display_name":"Thomas Schmickl","url":"https://kfunigraz.academia.edu/ThomasSchmickl"},"attachments":[{"id":115415417,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/115415417/thumbnails/1.jpg","file_name":"9956885.pdf","download_url":"https://www.academia.edu/attachments/115415417/download_file","bulk_download_file_name":"Strong_Emergence_Arising_from_Weak_Emerg.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/115415417/9956885-libre.pdf?1716935980=\u0026response-content-disposition=attachment%3B+filename%3DStrong_Emergence_Arising_from_Weak_Emerg.pdf\u0026Expires=1740594161\u0026Signature=XgxOdbrG-UKywAUjjo5WGRavixZBdx-eLmsPmGj5DBUVC4sy-UNAtLvsKdXMvTx7rG2tJmQ4no5SpJNSyxfRjuvU4PTnZtoKUKXyV-ECU5R0uLA2L96W1io60Ovh-f~B3BSqD5fwPqJK0WlqoZCVMWqchElD6ThTcx1av0aK1VqUWqvSADSeHp3W4l4FqI1uQOJrBBv85Oy7jO9ZT2fS4Y~dJEGq8b1S~tY6YerWZJRQq7h8N1rMeBRTERuj72xNhqz11FDj-HFmSR10xld-UbBNdonpjP324f1mbTQI6zzFe4u6E4r8gP-1~xTpUuM~ZqbfMbM~Olm4-ERQGmnCPQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="120181171"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/120181171/Forest_Fires_Fire_Management_and_the_Power_Law"><img alt="Research paper thumbnail of Forest Fires: Fire Management and the Power Law" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/120181171/Forest_Fires_Fire_Management_and_the_Power_Law">Forest Fires: Fire Management and the Power Law</a></div><div class="wp-workCard_item"><span>Springer eBooks</span><span>, 2020</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="120181171"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="120181171"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 120181171; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=120181171]").text(description); $(".js-view-count[data-work-id=120181171]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 120181171; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='120181171']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=120181171]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":120181171,"title":"Forest Fires: Fire Management and the Power Law","internal_url":"https://www.academia.edu/120181171/Forest_Fires_Fire_Management_and_the_Power_Law","owner_id":32562090,"coauthors_can_edit":true,"owner":{"id":32562090,"first_name":"Thomas","middle_initials":null,"last_name":"Schmickl","page_name":"ThomasSchmickl","domain_name":"kfunigraz","created_at":"2015-06-26T07:05:19.783-07:00","display_name":"Thomas Schmickl","url":"https://kfunigraz.academia.edu/ThomasSchmickl"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="120181170"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/120181170/Fundamentalism_in_a_social_learning_perspective_A_memetic_agent_model_of_vegetarianism_social_interaction_networks_and_food_markets"><img alt="Research paper thumbnail of Fundamentalism in a social learning perspective: A memetic agent model of vegetarianism, social interaction networks and food markets" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/120181170/Fundamentalism_in_a_social_learning_perspective_A_memetic_agent_model_of_vegetarianism_social_interaction_networks_and_food_markets">Fundamentalism in a social learning perspective: A memetic agent model of vegetarianism, social interaction networks and food markets</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Fundamentalism and extremism are behavioral traits prominently observed today, ranging from relig...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Fundamentalism and extremism are behavioral traits prominently observed today, ranging from religion and ideology to product choices and even dietary preferences. This study develops a multi-agent model depicting the exemplary case of preventing to eat meat (vegetarianism) or animal-derived products (veganism) as a set of “memes” that can evolve within a society. Behavioral traits can develop over time by means of (local) individual-based adaptation to an ultimate societal phenomenon by cultural (global) learning. The multi-agent model presented here predicts that fundamentalist strategies emerge in significant amounts only if certain extreme starting conditions of the environment (market) or of the initial population are met. When starting from non-extreme conditions, the population develops towards moderate behavioral traits and the market adapts to comfort these society-level adaptations. The underlying social network structure has a significant effect on those processes, as fundamentalism occurs only in fragmented subpopulations as longer-lasting phenomena. A very simple mechanism of social interaction is capable to capture general principles of the emergence of fundamentalist traits in societies.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="120181170"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="120181170"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 120181170; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); 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</script> <div class="js-work-strip profile--work_container" data-work-id="120181169"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/120181169/Morphogenesis_as_a_Collective_Decision_of_Agents_Competing_for_Limited_Resource_A_Plants_Approach"><img alt="Research paper thumbnail of Morphogenesis as a Collective Decision of Agents Competing for Limited Resource: A Plants Approach" class="work-thumbnail" src="https://attachments.academia-assets.com/115415425/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/120181169/Morphogenesis_as_a_Collective_Decision_of_Agents_Competing_for_Limited_Resource_A_Plants_Approach">Morphogenesis as a Collective Decision of Agents Competing for Limited Resource: A Plants Approach</a></div><div class="wp-workCard_item"><span>Lecture Notes in Computer Science</span><span>, 2018</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Competition for limited resource is a common concept in many artificial and natural collective sy...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Competition for limited resource is a common concept in many artificial and natural collective systems. In plants, the common resources-water, minerals and the products of photosynthesis-are a subject of competition for individual branches striving for growth. The competition is realized via a dynamic vascular system resulting in the dynamic morphology of the plant that is adapting to its environment. In this paper, a distributed morphogenesis algorithm inspired by the competition for limited resources in plants is described and is validated in directing the growth of a physical structure made out of braided modules. The effects of different parameters of the algorithm on the growth behavior of the structure are discussed analytically and similar effects are demonstrated in the physical system.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="45b5927ef9a1381f20a7101c16ec0b75" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":115415425,"asset_id":120181169,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/115415425/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="120181169"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="120181169"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 120181169; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=120181169]").text(description); $(".js-view-count[data-work-id=120181169]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 120181169; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='120181169']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="120181167"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/120181167/Vascular_Morphogenesis_Controller_A_Distributed_Controller_for_Growing_Artificial_Structures"><img alt="Research paper thumbnail of Vascular Morphogenesis Controller: A Distributed Controller for Growing Artificial Structures" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/120181167/Vascular_Morphogenesis_Controller_A_Distributed_Controller_for_Growing_Artificial_Structures">Vascular Morphogenesis Controller: A Distributed Controller for Growing Artificial Structures</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">It is a challenging task to develop morphologies of structures in response to dynamic environment...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">It is a challenging task to develop morphologies of structures in response to dynamic environmental factors and constraints. In the context of the EU-funded project flora robotica [1] we are interested in developing selforganized methods that combine local considerations and global requirements and drive the development of structures. Embryogenetic development of biological organisms and cell differentiation are studied for a long time in evolutionary developmental biology (EvoDevo) [2], [3]. Some of the mechanisms from that field are already applied to pattern formation [4] and development of body morphologies [5], [6] and controllers [7] in evolutionary robotics [8] and modular robotics [9]. In this work, vascular system and branching dynamics of plants are used as the source of inspiration for designing a novel algorithm called &quot;Vascular Morphogenesis Controller&quot; (VMC) that is applied to morphological development of modular structures. Plant vessels develop in the stems and roots. They transport water and minerals from the roots to the leaves, and sugars and photosynthates from the leaves to other parts of the plant [10]. There are evidences [11], [12] suggesting that there is a competition between different branches over the vascular growth. The branches that are in better situations (e.g., get more light) produce more photosynthates that flow back from the leaves. The higher flow rate leads to more vascular tissues in the branch and therefore more water and minerals from the roots reach the branch. More water and minerals facilitate the growth of the branch and the branch may end up in an even better situation which in turn reinforces the growth. Different branches with their different local conditions compete over production of new vessels. On the other hand, global resources (i.e., water) are limited and the vessels are subject to degradation as well. Based on the positive and negative feedback loops established by this competition and limitation, a dynamic system of vessels shape the growth of the plants.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="120181167"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="120181167"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 120181167; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); 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