Learning and adaptation of strategies in automated negotiations between context-aware agents

Autores
Kröhling, Dan Ezequiel; Chiotti, Omar Juan Alfredo; Martínez, Ernesto Carlos
Año de publicación
2024
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This work presents the hypothesis that guided the research efforts and a summary of the contributions of the doctoral thesis '`Aprendizaje y adaptación de estrategias para negociación automatizada entre agentes conscientes del contexto'. Succinctly, the thesis focuses on agents for automated bilateral negotiations that make use of the context as a key source of information to learn and adapt negotiation strategies in two levels of temporal abstraction. At the highest level, agents employ reinforcement learning to select strategies according to contextual circumstances. At the lowest level, agents use Gaussian Processes and artificial Theory of Mind to model their opponents and adapt their strategies. Agents are then tested in two Peer-to-Peer markets comprising an Eco-Industrial Park and a Smart Grid. The results highlight the significance for the automation of bilateral negotiations of incorporating the context as an informative source.
Fil: Kröhling, Dan Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Fil: Chiotti, Omar Juan Alfredo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Fil: Martínez, Ernesto Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Materia
Automated Negotiation
Multi-Agent Systems
Context-Awareness
Artificial Theory of Mind
Peer-to-Peer Markets
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/244558
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Learning and adaptation of strategies in automated negotiations between context-aware agentsKröhling, Dan EzequielChiotti, Omar Juan AlfredoMartínez, Ernesto CarlosAutomated NegotiationMulti-Agent SystemsContext-AwarenessArtificial Theory of MindPeer-to-Peer Marketshttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1This work presents the hypothesis that guided the research efforts and a summary of the contributions of the doctoral thesis '`Aprendizaje y adaptación de estrategias para negociación automatizada entre agentes conscientes del contexto'. Succinctly, the thesis focuses on agents for automated bilateral negotiations that make use of the context as a key source of information to learn and adapt negotiation strategies in two levels of temporal abstraction. At the highest level, agents employ reinforcement learning to select strategies according to contextual circumstances. At the lowest level, agents use Gaussian Processes and artificial Theory of Mind to model their opponents and adapt their strategies. Agents are then tested in two Peer-to-Peer markets comprising an Eco-Industrial Park and a Smart Grid. The results highlight the significance for the automation of bilateral negotiations of incorporating the context as an informative source.Fil: Kröhling, Dan Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Chiotti, Omar Juan Alfredo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Martínez, Ernesto Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaSociedad Iberoamericana de Inteligencia Artificial2024-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/244558Kröhling, Dan Ezequiel; Chiotti, Omar Juan Alfredo; Martínez, Ernesto Carlos; Learning and adaptation of strategies in automated negotiations between context-aware agents; Sociedad Iberoamericana de Inteligencia Artificial; Inteligencia Artificial; 27; 73; 2-2024; 159-1621988-3064CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://journal.iberamia.org/index.php/intartif/article/view/1305info:eu-repo/semantics/altIdentifier/doi/10.4114/intartif.vol27iss73pp159-162info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:06:06Zoai:ri.conicet.gov.ar:11336/244558instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:06:06.93CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Learning and adaptation of strategies in automated negotiations between context-aware agents
title Learning and adaptation of strategies in automated negotiations between context-aware agents
spellingShingle Learning and adaptation of strategies in automated negotiations between context-aware agents
Kröhling, Dan Ezequiel
Automated Negotiation
Multi-Agent Systems
Context-Awareness
Artificial Theory of Mind
Peer-to-Peer Markets
title_short Learning and adaptation of strategies in automated negotiations between context-aware agents
title_full Learning and adaptation of strategies in automated negotiations between context-aware agents
title_fullStr Learning and adaptation of strategies in automated negotiations between context-aware agents
title_full_unstemmed Learning and adaptation of strategies in automated negotiations between context-aware agents
title_sort Learning and adaptation of strategies in automated negotiations between context-aware agents
dc.creator.none.fl_str_mv Kröhling, Dan Ezequiel
Chiotti, Omar Juan Alfredo
Martínez, Ernesto Carlos
author Kröhling, Dan Ezequiel
author_facet Kröhling, Dan Ezequiel
Chiotti, Omar Juan Alfredo
Martínez, Ernesto Carlos
author_role author
author2 Chiotti, Omar Juan Alfredo
Martínez, Ernesto Carlos
author2_role author
author
dc.subject.none.fl_str_mv Automated Negotiation
Multi-Agent Systems
Context-Awareness
Artificial Theory of Mind
Peer-to-Peer Markets
topic Automated Negotiation
Multi-Agent Systems
Context-Awareness
Artificial Theory of Mind
Peer-to-Peer Markets
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv This work presents the hypothesis that guided the research efforts and a summary of the contributions of the doctoral thesis '`Aprendizaje y adaptación de estrategias para negociación automatizada entre agentes conscientes del contexto'. Succinctly, the thesis focuses on agents for automated bilateral negotiations that make use of the context as a key source of information to learn and adapt negotiation strategies in two levels of temporal abstraction. At the highest level, agents employ reinforcement learning to select strategies according to contextual circumstances. At the lowest level, agents use Gaussian Processes and artificial Theory of Mind to model their opponents and adapt their strategies. Agents are then tested in two Peer-to-Peer markets comprising an Eco-Industrial Park and a Smart Grid. The results highlight the significance for the automation of bilateral negotiations of incorporating the context as an informative source.
Fil: Kröhling, Dan Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Fil: Chiotti, Omar Juan Alfredo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Fil: Martínez, Ernesto Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
description This work presents the hypothesis that guided the research efforts and a summary of the contributions of the doctoral thesis '`Aprendizaje y adaptación de estrategias para negociación automatizada entre agentes conscientes del contexto'. Succinctly, the thesis focuses on agents for automated bilateral negotiations that make use of the context as a key source of information to learn and adapt negotiation strategies in two levels of temporal abstraction. At the highest level, agents employ reinforcement learning to select strategies according to contextual circumstances. At the lowest level, agents use Gaussian Processes and artificial Theory of Mind to model their opponents and adapt their strategies. Agents are then tested in two Peer-to-Peer markets comprising an Eco-Industrial Park and a Smart Grid. The results highlight the significance for the automation of bilateral negotiations of incorporating the context as an informative source.
publishDate 2024
dc.date.none.fl_str_mv 2024-02
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/244558
Kröhling, Dan Ezequiel; Chiotti, Omar Juan Alfredo; Martínez, Ernesto Carlos; Learning and adaptation of strategies in automated negotiations between context-aware agents; Sociedad Iberoamericana de Inteligencia Artificial; Inteligencia Artificial; 27; 73; 2-2024; 159-162
1988-3064
CONICET Digital
CONICET
url http://hdl.handle.net/11336/244558
identifier_str_mv Kröhling, Dan Ezequiel; Chiotti, Omar Juan Alfredo; Martínez, Ernesto Carlos; Learning and adaptation of strategies in automated negotiations between context-aware agents; Sociedad Iberoamericana de Inteligencia Artificial; Inteligencia Artificial; 27; 73; 2-2024; 159-162
1988-3064
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://journal.iberamia.org/index.php/intartif/article/view/1305
info:eu-repo/semantics/altIdentifier/doi/10.4114/intartif.vol27iss73pp159-162
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Sociedad Iberoamericana de Inteligencia Artificial
publisher.none.fl_str_mv Sociedad Iberoamericana de Inteligencia Artificial
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.069144

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