Acquisition of a concession strategy in multi-issue negotiation

Yoshiaki Yasumura, Takahiko Kamiryo, Shohei Yoshikawa, Kuniaki Uehara

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

This paper presents a method for acquiring a concession 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 the 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 a punishment of negotiation breakdown. The experimental results showed that the agents could acquire the 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
Pages (from-to)161-171
Number of pages11
JournalWeb Intelligence and Agent Systems
Volume7
Issue number2
DOIs
Publication statusPublished - 2009 Aug 12
Externally publishedYes

Keywords

  • Concession strategy
  • Multi-issue negotiation
  • Reinforcement learning
  • Win-win negotiation

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Artificial Intelligence

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