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height="287" /> <h2> </h2> <h2>Scope</h2> <p style="text-align: justify;">IEEE Transactions on Evolutionary Computation (TEVC) publishes archival-quality original papers in evolutionary computation and related areas including nature-inspired algorithms, population-based methods, and optimization where selection and variation are integral, and hybrid systems where these paradigms are combined. Purely theoretical papers are considered as are application papers that provide general insights into these areas of computation.</p> <p style="text-align: justify;">The IEEE TEVC, published six times a year, publishes archival-quality original papers in evolutionary computation and related areas including nature-inspired algorithms, population-based methods, and optimization where selection and variation are integral, and hybrid systems where these paradigms are combined. Purely theoretical papers are considered as are application papers that provide general insights into these areas of computation.</p> <p align="center"><a href="https://www.ieee.org/membership-catalog/productdetail/showProductDetailPage.html?product=PER170-ELE&searchResults=Y"><button class="btn btn-danger btn-lg" type="button">Subscribe</button> </a><a href="https://ieee.atyponrex.com/journal/TEVC-IEEE"><button class="btn btn-danger btn-lg" type="button">Submit Manuscript</button></a> <a href="https://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=4235"><button class="btn btn-danger btn-lg" type="button">View Current Issue</button></a></p> <h3>Impact Score</h3> <p><a href="https://ieeexplore.ieee.org/Xplorehelp/overview-of-ieee-xplore/about-content#citescore"><img style="width: 560px; height: 102px;" src="/images/files/Publications/impact-scores/tnnls_2024.JPG" alt="tnnls 2024" data-mce-width="560" data-mce-height="102" /></a></p> <p style="text-align: justify;">The values displayed for the journal bibliometrics fields in IEEE Xplore are based on the Journal Citation Report from Clarivate from the 2023 report released in June 2024. Journal Citation Metrics Journal Citation Metrics such as Impact Factor, Eigenfactor Score™ and Article Influence Score™ are available where applicable. Each year, Journal Citation Reports© (JCR) from Thomson Reuters examines the influence and impact of scholarly research journals. JCR reveals the relationship between citing and cited journals, offering a systematic, objective means to evaluate the world's leading journals. Find out more about <a href="https://ieeexplore.ieee.org/Xplorehelp/overview-of-ieee-xplore/about-content#journal-citation-metrics" target="_blank" rel="noopener">IEEE Journal Rankings</a>.</p> <h3>Featured Paper</h3> <p><b>Evaluation of Frameworks That Combine Evolution and Learning to Design Robots in Complex Morphological Spaces</b></p> <p><i>Authors</i>: Wei Li; Edgar Buchanan; Léni K. Le Goff; Emma Hart; Matthew F. Hale; Bingsheng Wei <br /> <i>Publication</i>: IEEE Transactions on Evolutionary Computation (TEVC)<br /> <i>Issue</i>: Volume 28, Issue 6 – December 2024<br /> <i>Pages</i>: 1561 - 1574</p> <p style="text-align: justify;"><i>Abstract</i>: Jointly optimizing both the body and brain of a robot is known to be a challenging task, especially when attempting to evolve designs in simulation that will subsequently be built in the real world. To address this, it is increasingly common to combine evolution with a learning algorithm that can either improve the inherited controllers of new offspring to fine tune them to the new body design or learn them from scratch. In this article an approach is proposed in which a robot is specified indirectly by two compositional pattern producing networks (CPPNs) encoded in a single genome, one which encodes the brain and the other the body. The body part of the genome is evolved using an evolutionary algorithm (EA), with an individual learning algorithm (also an EA) applied to the inherited controller to improve it. The goal of this article is to determine how to utilize the results of learning process most effectively to improve task performance of the robot. Specifically, three variants are investigated: 1) evolution of the body+controller only; 2) a learning algorithm is applied to the inherited controller with the learned fitness assigned to the genome; and 3) learning is applied and the genome is updated with the learned controller, as well as being assigned the learned fitness. Experiments are performed in three different scenarios chosen to favor different bodies and locomotion patterns. It is shown that better performance can be obtained using learning but only if the learned controller is inherited by the offspring.</p> <p><i>Index Terms</i>: Robots, Robot sensing systems, Robot kinematics, Genomics, Bioinformatics, Sensors, Morphology<br /><em>IEEE Xplore Link</em>: <a href="https://ieeexplore.ieee.org/document/10349126">https://ieeexplore.ieee.org/document/8456559</a><a href="https://ieeexplore.ieee.org/document/8657776"></a></p> </div> </div> <div class="clearfix"></div></article> <div id="content-column-1" class="col-md-3 col-md-pull-9"> <hr class="visible-sm-block visible-xs-block" /> <ul class="nav navbar-nav menu"> <li id="secondary-nav" class="menu-title visible-sm visible-xs">IEEE Transactions on Evolutionary Computation </li><li class="item-654 child"><a href="/publications/t-evolutionary-computation/ieee-tevc" ><span>IEEE TEVC</span></a></li><li class="item-597 child"><a href="/publications/t-evolutionary-computation/welcome-from-the-vice-president-for-publications" ><span>Welcome from the Vice President for Publications</span></a></li><li class="item-378 child"><a href="/publications/t-evolutionary-computation/tevc-editor-and-associate-editors" ><span>Editor and Associate Editors</span></a></li><li class="item-379 child"><a href="http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=4235" ><span>IEEE Xplore (TEVC)</span></a></li><li class="item-380 child"><a href="/publications/t-evolutionary-computation/tevc-information-for-authors" ><span>Information for Authors</span></a></li><li class="item-381 child"><a href="/publications/t-evolutionary-computation/tevc-guidelines-for-paper-submission" ><span>Guidelines for Paper Submission</span></a></li><li class="item-382 child"><a href="/publications/t-evolutionary-computation/tevc-types-of-contributions" ><span>Types of Contributions</span></a></li><li class="item-385 child"><a href="/publications/t-evolutionary-computation/tevc-ieee-copyright" ><span>IEEE Copyright</span></a></li><li class="item-386 child"><a href="/publications/t-evolutionary-computation/tevc-page-charges" ><span>Page Charges</span></a></li><li class="item-390 child"><a href="/publications/t-evolutionary-computation/tevc-professional-editing-services" ><span>Professional Editing Services</span></a></li><li class="item-391 child"><a href="/publications/t-evolutionary-computation/tevc-plagiarism-and-ethical-issues" ><span>Plagiarism and Ethical Issues</span></a></li><li class="item-392 child"><a href="/publications/t-evolutionary-computation/tevc-arxiv" ><span>Arxiv</span></a></li><li class="item-393 child"><a href="http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=4235" ><span>Recent Articles</span></a></li><li class="item-394 child"><a href="http://ieeexplore.ieee.org/xpl/topAccessedArticles.jsp?punumber=4235" ><span>Most Accessed Articles</span></a></li><li class="item-395 child"><a href="/publications/t-evolutionary-computation/tevc-special-issues" ><span>Special Issues</span></a></li><li class="item-396 child"><a href="/publications/t-evolutionary-computation/tevc-featured-paper" ><span>Featured Paper</span></a></li><li class="item-397 child"><a href="http://advertise.ieee.org/product-advertising-view-all/ieee-computational-intelligence-magazine-print-digital/" ><span>Advertising</span></a></li></ul> </div> </div> </div> </div>  <footer class="hidden-print"> <div class="container"> <div class="row"> <div class="col-md-12"> <hr class="footer-separator"> </div> </div> <div class="custom" > <footer class="custom-footer container"> <div class="row"> <div class="col-md-6"> <ul class="list-inline"> <li><a href="https://ieee-cis.blogspot.co.uk/"><i class="fa fa-rss social-icon fa-lg"></i>  </a></li> <li><a href="https://twitter.com/ieeecis"><i class="fa fa-facebook social-icon fa-lg"></i>  | <img style="width: 15px; 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