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                     <mods:roleTerm type="text">author</mods:roleTerm>
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                  <mods:namePart>Papadopoulos, Nikolaos</mods:namePart>
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                  <mods:dateIssued encoding="iso8601">2021-01-26T11:39:23Z2021-01-26T11:39:23Z2020-07</mods:dateIssued>
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               <mods:abstract>Treball fi de màster de: Master in Cognitive Systems and Interactive MediaDirectos: Martí Sànchez-Fibla, Ismael Tito Freire GonzalezIn this thesis, a novel performance evaluation framework is introduced for several&#xd;
dynamic multi-agent interpretations of the Battle of the Exes scenario, which are also&#xd;
proposed for the first time. The Multi-Agent BoE scenario (MBoE) was modeled as a&#xd;
Markov Game and was computationally examined in 7 branches of 2-6 and 2-10 agents’&#xd;
experiments (43 experiments) for two types of state-representations, two numbers of&#xd;
episodes and various reward systems. New variations of Fairness (Multi-agent Fairness&#xd;
&amp;amp; Reward Fairness) were proposed, with the latter being used to measure the systems’&#xd;
performance, as literature’s 2-agents metrics were found insufficient for n-agents&#xd;
games. Furthermore, a Perfect Alternation equilibrium was introduced, defined and&#xd;
evaluated, as an ideal equilibrium, robust to the number of agents and episodes of a&#xd;
system. For the purposes of this thesis, it was hypothesized and eventually shown, that a&#xd;
Fair and Efficient equilibrium in multi-agent dynamic environments such as MBoE does&#xd;
not necessarily signify Perfect Alternation. Furthermore, new types of metrics and&#xd;
indicators for measuring and evaluating the performance of a system towards Perfect&#xd;
Alternation were introduced and tested: Rotation (RT, with 2 sub-metrics and 2 forms),&#xd;
Alternation (ALT, 6 versions) and Proportional Individual Performance. ALT metrics&#xd;
definitions were found sufficient for evaluating of Perfect Alternation, thus they was&#xd;
benchmarked and tested through the series of experiments, aspiring to initiate this&#xd;
branch of studies and contribute novel tools for deeper understanding of complexsystems, such as the social behavior of cognitive systems.</mods:abstract>
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               <mods:accessCondition type="useAndReproduction">This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License http://creativecommons.org/licenses/by-nc-nd/4.0 info:eu-repo/semantics/openAccess</mods:accessCondition>
               <mods:subject>
                  <mods:topic>Conventionalization</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Game Theory</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Battle of the Exes</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Battle of the Sexes</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Multi-agent Battle of the Exes</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>MBoE</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Repeated Games</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Repeated Games</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Stochastic Games</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Alternation Equilibrium</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>n-agents</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Multi-Agent Reinforcement Learning</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Q-learning</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Perfect Alternation Equilibrium</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Perfect Alternation</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Fairness</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Efficiency</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Reward Fairness</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Multi-agent Fairness</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Rotation</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Metric</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>Alternation Metric</mods:topic>
               </mods:subject>
               <mods:subject>
                  <mods:topic>ALT</mods:topic>
               </mods:subject>
               <mods:titleInfo>
                  <mods:title>Study of turn-taking coordination for nagents in game-theoretic scenarios, with reinforcement learning: Proposal of an evaluation framework of Perfect Alternation Equilibria for multi-agent environments</mods:title>
               </mods:titleInfo>
               <mods:genre>info:eu-repo/semantics/masterThesis</mods:genre>
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