Strategy acquisition on multi-issue negotiation without estimating opponent's preference

Shohei Yoshikawa, Yoshiaki Yasumura, Kuniaki Uehara

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

1 Citation (Scopus)

Abstract

In multi-issue negotiation, an opponent's preference is rarely open. Under this environment, it is difficult to acquire a negotiation result that realizes win-win negotiation. In this paper, we present a novel method for realizing win-win negotiation although an opponent's preference is not open. In this method, an agent learns how to make a concession to an opponent. To learn the concession strategy, we adopt reinforcement learning. In reinforcement learning, the agent recognizes a negotiation state to each issue in negotiation. According to the state, the agent makes a proposal to increase own profit. A reward of the learning is a profit of an agreement and punishment of negotiation breakdown. Experimental results showed that agents could acquire a negotiation strategy that avoids negotiation breakdown and increases profits of both sides. Finally, the agents can acquire the action policy that strikes a balance between cooperation and competition.

Original languageEnglish
Title of host publicationAgent and Multi-Agent Systems
Subtitle of host publicationTechnologies and Applications - Second KES International Symposium, KES-AMSTA 2008, Proceedings
Pages371-380
Number of pages10
DOIs
Publication statusPublished - 2008 Jul 21
Externally publishedYes
Event2nd KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications, KES-AMSTA 2008 - Incheon, Korea, Republic of
Duration: 2008 Mar 262008 Mar 28

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4953 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications, KES-AMSTA 2008
CountryKorea, Republic of
CityIncheon
Period08/3/2608/3/28

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Yoshikawa, S., Yasumura, Y., & Uehara, K. (2008). Strategy acquisition on multi-issue negotiation without estimating opponent's preference. In Agent and Multi-Agent Systems: Technologies and Applications - Second KES International Symposium, KES-AMSTA 2008, Proceedings (pp. 371-380). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4953 LNAI). https://doi.org/10.1007/978-3-540-78582-8_38