The importance of context-dependent learning in negotiation agents

Autores
Kröhling, Dan; Hernández, Federico; Martínez, Ernesto; Chiotti, Omar Juan Alfredo
Año de publicación
2018
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Automated negotiation between arti cial agents is essential to deploy Cognitive Computing and Internet of Things. The behavior of a negotiating agent depends signi cantly on the in uence of environmental conditions or contextual variables, since they affect not only a given agent preferences and strategies, but also those of other agents. Despite this, the existing literature on automated negotiation is scarce about how to properly account for the effect of context-relevant variables in learning and evolving strategies. In this paper, a novel context-driven representation for automated negotiation is proposed. Also, a simple negotiating agent that queries available information from its environment, internally models contextual variables, and learns how to take advantage of this knowledge by playing against himself using reinforcement learning is proposed. Through a set of episodes against negotiating agents in the existing literature, it is shown that it makes no sense to negotiate without taking context-relevant variables into account. The context-aware negotiating agent has been implemented in the GENIUS negotiation environment, and results obtained are signi cant and revealing.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
agents
automated negotiation
negotiation intelligence
Internet of Things
reinforcement learning
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-sa/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/70684
Acceder
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network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling The importance of context-dependent learning in negotiation agentsKröhling, DanHernández, FedericoMartínez, ErnestoChiotti, Omar Juan AlfredoCiencias Informáticasagentsautomated negotiationnegotiation intelligenceInternet of Thingsreinforcement learningAutomated negotiation between arti cial agents is essential to deploy Cognitive Computing and Internet of Things. The behavior of a negotiating agent depends signi cantly on the in uence of environmental conditions or contextual variables, since they affect not only a given agent preferences and strategies, but also those of other agents. Despite this, the existing literature on automated negotiation is scarce about how to properly account for the effect of context-relevant variables in learning and evolving strategies. In this paper, a novel context-driven representation for automated negotiation is proposed. Also, a simple negotiating agent that queries available information from its environment, internally models contextual variables, and learns how to take advantage of this knowledge by playing against himself using reinforcement learning is proposed. Through a set of episodes against negotiating agents in the existing literature, it is shown that it makes no sense to negotiate without taking context-relevant variables into account. The context-aware negotiating agent has been implemented in the GENIUS negotiation environment, and results obtained are signi cant and revealing.Sociedad Argentina de Informática e Investigación Operativa2018-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf1-14http://sedici.unlp.edu.ar/handle/10915/70684enginfo:eu-repo/semantics/altIdentifier/url/http://47jaiio.sadio.org.ar/sites/default/files/ASAI-01.pdfinfo:eu-repo/semantics/altIdentifier/issn/2451-7585info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-sa/3.0/Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:11:20Zoai:sedici.unlp.edu.ar:10915/70684Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:11:20.68SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv The importance of context-dependent learning in negotiation agents
title The importance of context-dependent learning in negotiation agents
spellingShingle The importance of context-dependent learning in negotiation agents
Kröhling, Dan
Ciencias Informáticas
agents
automated negotiation
negotiation intelligence
Internet of Things
reinforcement learning
title_short The importance of context-dependent learning in negotiation agents
title_full The importance of context-dependent learning in negotiation agents
title_fullStr The importance of context-dependent learning in negotiation agents
title_full_unstemmed The importance of context-dependent learning in negotiation agents
title_sort The importance of context-dependent learning in negotiation agents
dc.creator.none.fl_str_mv Kröhling, Dan
Hernández, Federico
Martínez, Ernesto
Chiotti, Omar Juan Alfredo
author Kröhling, Dan
author_facet Kröhling, Dan
Hernández, Federico
Martínez, Ernesto
Chiotti, Omar Juan Alfredo
author_role author
author2 Hernández, Federico
Martínez, Ernesto
Chiotti, Omar Juan Alfredo
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
agents
automated negotiation
negotiation intelligence
Internet of Things
reinforcement learning
topic Ciencias Informáticas
agents
automated negotiation
negotiation intelligence
Internet of Things
reinforcement learning
dc.description.none.fl_txt_mv Automated negotiation between arti cial agents is essential to deploy Cognitive Computing and Internet of Things. The behavior of a negotiating agent depends signi cantly on the in uence of environmental conditions or contextual variables, since they affect not only a given agent preferences and strategies, but also those of other agents. Despite this, the existing literature on automated negotiation is scarce about how to properly account for the effect of context-relevant variables in learning and evolving strategies. In this paper, a novel context-driven representation for automated negotiation is proposed. Also, a simple negotiating agent that queries available information from its environment, internally models contextual variables, and learns how to take advantage of this knowledge by playing against himself using reinforcement learning is proposed. Through a set of episodes against negotiating agents in the existing literature, it is shown that it makes no sense to negotiate without taking context-relevant variables into account. The context-aware negotiating agent has been implemented in the GENIUS negotiation environment, and results obtained are signi cant and revealing.
Sociedad Argentina de Informática e Investigación Operativa
description Automated negotiation between arti cial agents is essential to deploy Cognitive Computing and Internet of Things. The behavior of a negotiating agent depends signi cantly on the in uence of environmental conditions or contextual variables, since they affect not only a given agent preferences and strategies, but also those of other agents. Despite this, the existing literature on automated negotiation is scarce about how to properly account for the effect of context-relevant variables in learning and evolving strategies. In this paper, a novel context-driven representation for automated negotiation is proposed. Also, a simple negotiating agent that queries available information from its environment, internally models contextual variables, and learns how to take advantage of this knowledge by playing against himself using reinforcement learning is proposed. Through a set of episodes against negotiating agents in the existing literature, it is shown that it makes no sense to negotiate without taking context-relevant variables into account. The context-aware negotiating agent has been implemented in the GENIUS negotiation environment, and results obtained are signi cant and revealing.
publishDate 2018
dc.date.none.fl_str_mv 2018-09
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
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http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/70684
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dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://47jaiio.sadio.org.ar/sites/default/files/ASAI-01.pdf
info:eu-repo/semantics/altIdentifier/issn/2451-7585
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-sa/3.0/
Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0)
dc.format.none.fl_str_mv application/pdf
1-14
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instname:Universidad Nacional de La Plata
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instname_str Universidad Nacional de La Plata
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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