Strategy acquisition of agents in multi-issue negotiation

Shohei Yoshikawa, Takahiko Kamiryo, Yoshiaki Yasumura, Kuniaki Uehara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

This paper presents a method for acquiring a strategy of an agent in multi-issue negotiation. This method learns how to make a concession to an opponent for realizing win-win negotiation. To learn the concession strategy, we adopt reinforcement learning. First, an agent receives a proposal from an opponent. The agent recognizes a negotiation state using the difference between their proposals and difference between their concessions. According to the state, the agent makes a proposal by reinforcement learning. A reward of the learning is a profit of an agreement and punishment of negotiation breakdown. The experimental results showed that agents could acquire a negotiation strategy that avoids negotiation breakdown and increases profits of an agreement. As a result, agents can acquire the action policy that strikes a balance between cooperation and competition.

Original languageEnglish
Title of host publicationProceedings - 2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2006 Main Conference Proceedings), WI'06
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages933-939
Number of pages7
ISBN (Print)0769527477, 9780769527475
DOIs
Publication statusPublished - 2006 Jan 1
Externally publishedYes
Event2006 IEEE/WIC/ACM International Conference on Web Intelligence, WI'06 - Hong Kong, China
Duration: 2006 Dec 182006 Dec 22

Publication series

NameProceedings - 2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2006 Main Conference Proceedings), WI'06

Conference

Conference2006 IEEE/WIC/ACM International Conference on Web Intelligence, WI'06
Country/TerritoryChina
CityHong Kong
Period06/12/1806/12/22

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software

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