Conference paper Open Access

Aspiration-based Perturbed Learning Automata

Chasparis, Georgios


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  <identifier identifierType="DOI">10.5281/zenodo.1186662</identifier>
  <creators>
    <creator>
      <creatorName>Chasparis, Georgios</creatorName>
      <givenName>Georgios</givenName>
      <familyName>Chasparis</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-3059-3575</nameIdentifier>
      <affiliation>Software Competence Center Hagenberg GmbH</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Aspiration-based Perturbed Learning Automata</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2018</publicationYear>
  <subjects>
    <subject>Learning automata, distributed optimization, coordination games</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2018-03-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Conference paper</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/1186662</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.1186661</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;This paper introduces a novel payoff-based learning scheme for distributed optimization in repeatedly-played strategic-form games. Standard reinforcement-based learning exhibits several limitations with respect to their asymptotic stability. For example, in two-player coordination games, payoff-dominant (or efficient) Nash equilibria may not be stochastically stable. In this work, we present an extension of perturbed learning automata, namely aspiration-based perturbed learning automata (APLA) that overcomes these limitations. We provide a stochastic stability analysis in multi-player coordination games. In the case of two-player coordination games, we show that the payoff-dominant Nash equilibrium is the unique stochastically stable state.&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/644235/">644235</awardNumber>
      <awardTitle>REfactoring Parallel Heterogeneous Resource-Aware Applications  - a Software Engineering Approach</awardTitle>
    </fundingReference>
  </fundingReferences>
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