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<button class="button is-small is-link">Go</button> </div> </div> </form> </div> </div> <ol class="breathe-horizontal" start="1"> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2109.08461">arXiv:2109.08461</a> <span> [<a href="https://arxiv.org/pdf/2109.08461">pdf</a>, <a href="https://arxiv.org/format/2109.08461">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computer Science and Game Theory">cs.GT</span> </div> </div> <p class="title is-5 mathjax"> Beyond identical utilities: buyer utility functions and fair allocations </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Camacho%2C+F">Franklin Camacho</a>, <a href="/search/cs?searchtype=author&query=Fonseca-Delgado%2C+R">Rigoberto Fonseca-Delgado</a>, <a href="/search/cs?searchtype=author&query=P%C3%A9rez%2C+R+P">Ram贸n Pino P茅rez</a>, <a href="/search/cs?searchtype=author&query=Tapia%2C+G">Guido Tapia</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2109.08461v1-abstract-short" style="display: inline;"> The problem of finding envy-free allocations of indivisible goods can not always be solved; therefore, it is common to study some relaxations such as envy-free up to one good (EF1). Another property of interest for efficiency of an allocation is the Pareto Optimality (PO). Under additive utility functions, it is possible to find allocations EF1 and PO using Nash social welfare. However, to find an… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2109.08461v1-abstract-full').style.display = 'inline'; document.getElementById('2109.08461v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2109.08461v1-abstract-full" style="display: none;"> The problem of finding envy-free allocations of indivisible goods can not always be solved; therefore, it is common to study some relaxations such as envy-free up to one good (EF1). Another property of interest for efficiency of an allocation is the Pareto Optimality (PO). Under additive utility functions, it is possible to find allocations EF1 and PO using Nash social welfare. However, to find an allocation that maximizes the Nash social welfare is a computationally hard problem. In this work we propose a polynomial time algorithm which maximizes the utilitarian social welfare and at the same time produces an allocation which is EF1 and PO in a special case of additive utility functions called buyer utility functions. Moreover, a slight modification of our algorithm produces an allocation which is envy-free up to any positively valued good (EFX). <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2109.08461v1-abstract-full').style.display = 'none'; document.getElementById('2109.08461v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 17 September, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> September 2021. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">20 pages, 1 figure</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">MSC Class:</span> 91B32 <span class="has-text-black-bis has-text-weight-semibold">ACM Class:</span> G.2.3 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2108.00802">arXiv:2108.00802</a> <span> [<a href="https://arxiv.org/pdf/2108.00802">pdf</a>, <a href="https://arxiv.org/ps/2108.00802">ps</a>, <a href="https://arxiv.org/format/2108.00802">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Systems and Control">eess.SY</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Multiagent Systems">cs.MA</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Optimization and Control">math.OC</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1109/TAC.2018.2792301">10.1109/TAC.2018.2792301 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Coalitional Control for Self-Organizing Agents </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Fele%2C+F">Filiberto Fele</a>, <a href="/search/cs?searchtype=author&query=Debada%2C+E">Ezequiel Debada</a>, <a href="/search/cs?searchtype=author&query=Maestre%2C+J+M">Jos茅 M. Maestre</a>, <a href="/search/cs?searchtype=author&query=Camacho%2C+E+F">Eduardo F. Camacho</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2108.00802v1-abstract-short" style="display: inline;"> Coalitional control is concerned with the management of multi-agent systems where cooperation cannot be taken for granted (due to, e.g., market competition, logistics). This paper proposes a model predictive control (MPC) framework aimed at large-scale dynamically-coupled systems whose individual components, possessing a limited model of the system, are controlled independently, pursuing possibly… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2108.00802v1-abstract-full').style.display = 'inline'; document.getElementById('2108.00802v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2108.00802v1-abstract-full" style="display: none;"> Coalitional control is concerned with the management of multi-agent systems where cooperation cannot be taken for granted (due to, e.g., market competition, logistics). This paper proposes a model predictive control (MPC) framework aimed at large-scale dynamically-coupled systems whose individual components, possessing a limited model of the system, are controlled independently, pursuing possibly competing objectives. The emergence of cooperating clusters of controllers is contemplated through an autonomous negotiation protocol, based on the characterization as a coalitional game of the benefit derived by a broader feedback and the alignment of the individual objectives. Specific mechanisms for the cooperative benefit redistribution that relax the cognitive requirements of the game are employed to compensate for possible local cost increases due to cooperation. As a result, the structure of the overall MPC feedback can be adapted online to the degree of interaction between different parts of the system, while satisfying the individual interests of the agents. A wide-area control application for the power grid with the objective of minimizing frequency deviations and undesired inter-area power transfers is used as study case. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2108.00802v1-abstract-full').style.display = 'none'; document.getElementById('2108.00802v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 2 August, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2021. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">14 pages, 8 figures</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> in IEEE Transactions on Automatic Control, vol. 63, no. 9, pp. 2883-2897, Sept. 2018 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1805.06864">arXiv:1805.06864</a> <span> [<a href="https://arxiv.org/pdf/1805.06864">pdf</a>, <a href="https://arxiv.org/ps/1805.06864">ps</a>, <a href="https://arxiv.org/format/1805.06864">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computer Science and Game Theory">cs.GT</span> </div> </div> <p class="title is-5 mathjax"> Resource allocation under uncertainty: an algebraic and qualitative treatment </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Camacho%2C+F">Franklin Camacho</a>, <a href="/search/cs?searchtype=author&query=Chac%C3%B3n%2C+G">Gerardo Chac贸n</a>, <a href="/search/cs?searchtype=author&query=Per%C3%A9z%2C+R+P">Ram贸n Pino Per茅z</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1805.06864v1-abstract-short" style="display: inline;"> We use an algebraic viewpoint, namely a matrix framework to deal with the problem of resource allocation under uncertainty in the context of a qualitative approach. Our basic qualitative data are a plausibility relation over the resources, a hierarchical relation over the agents and of course the preference that the agents have over the resources. With this data we propose a qualitative binary rel… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1805.06864v1-abstract-full').style.display = 'inline'; document.getElementById('1805.06864v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1805.06864v1-abstract-full" style="display: none;"> We use an algebraic viewpoint, namely a matrix framework to deal with the problem of resource allocation under uncertainty in the context of a qualitative approach. Our basic qualitative data are a plausibility relation over the resources, a hierarchical relation over the agents and of course the preference that the agents have over the resources. With this data we propose a qualitative binary relation $\unrhd$ between allocations such that $\mathcal{F}\unrhd \mathcal{G}$ has the following intended meaning: the allocation $\mathcal{F}$ produces more or equal social welfare than the allocation $\mathcal{G}$. We prove that there is a family of allocations which are maximal with respect to $\unrhd$. We prove also that there is a notion of simple deal such that optimal allocations can be reached by sequences of simple deals. Finally, we introduce some mechanism for discriminating {optimal} allocations. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1805.06864v1-abstract-full').style.display = 'none'; document.getElementById('1805.06864v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 17 May, 2018; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> May 2018. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">MSC Class:</span> 90A80; 68T; 68T37; 68E; 90A06 </p> </li> </ol> <div class="is-hidden-tablet">  <span class="help" style="display: inline-block;"><a href="https://github.com/arXiv/arxiv-search/releases">Search v0.5.6 released 2020-02-24</a>  </span> </div> </div> </main> <footer> <div class="columns is-desktop" role="navigation" aria-label="Secondary">  <div class="column"> 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