Harnessing Implicit Cooperation: A Multi-Agent Reinforcement Learning Approach Towards Decentralized Local Energy Markets

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dc.contributor.authorNelson Salazar-Peña
dc.contributor.authorAlejandra Tabares
dc.contributor.authorAndrés González-Mancera
dc.coverage.spatialBolivia
dc.date.accessioned2026-03-22T20:52:52Z
dc.date.available2026-03-22T20:52:52Z
dc.date.issued2026
dc.identifier.doi10.2139/ssrn.6150849
dc.identifier.urihttps://doi.org/10.2139/ssrn.6150849
dc.identifier.urihttps://andeanlibrary.org/handle/123456789/84620
dc.publisherRELX Group (Netherlands)
dc.relation.ispartofSSRN Electronic Journal
dc.sourceUniversidad de Los Andes
dc.subjectDecentralised system
dc.subjectComputer science
dc.subjectReinforcement learning
dc.subjectBenchmark (surveying)
dc.subjectContext (archaeology)
dc.subjectGrid
dc.subjectMathematical optimization
dc.subjectStability (learning theory)
dc.subjectDistributed computing
dc.subjectMarkov decision process
dc.titleHarnessing Implicit Cooperation: A Multi-Agent Reinforcement Learning Approach Towards Decentralized Local Energy Markets
dc.typepreprint

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