The importance of context-dependent learning in negotiation agents

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 str...

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Autores principales: Kröhling, Dan, Hernández, Federico, Martínez, Ernesto, Chiotti, Omar Juan Alfredo
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2018
Materias:
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/70684
http://47jaiio.sadio.org.ar/sites/default/files/ASAI-01.pdf
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id I19-R120-10915-70684
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
agents
automated negotiation
negotiation intelligence
Internet of Things
reinforcement learning
spellingShingle Ciencias Informáticas
agents
automated negotiation
negotiation intelligence
Internet of Things
reinforcement learning
Kröhling, Dan
Hernández, Federico
Martínez, Ernesto
Chiotti, Omar Juan Alfredo
The importance of context-dependent learning in negotiation agents
topic_facet Ciencias Informáticas
agents
automated negotiation
negotiation intelligence
Internet of Things
reinforcement learning
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.
format Objeto de conferencia
Objeto de conferencia
author Kröhling, Dan
Hernández, Federico
Martínez, Ernesto
Chiotti, Omar Juan Alfredo
author_facet Kröhling, Dan
Hernández, Federico
Martínez, Ernesto
Chiotti, Omar Juan Alfredo
author_sort Kröhling, Dan
title The importance of context-dependent learning in negotiation agents
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 importance of context-dependent learning in negotiation agents
publishDate 2018
url http://sedici.unlp.edu.ar/handle/10915/70684
http://47jaiio.sadio.org.ar/sites/default/files/ASAI-01.pdf
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