A genetic agent-based negotiation system

Samuel P.M. Choi*, Jiming LIU, Sheung Ping Chan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

109 Citations (Scopus)

Abstract

Automated negotiation has become increasingly important since the advent of electronic commerce. Nowadays, goods are no longer necessarily traded at a fixed price, and instead buyers and sellers negotiate among themselves to reach a deal that maximizes the payoffs of both parties. In this paper, a genetic agent-based model for bilateral, multi-issue negotiation is studied. The negotiation agent employs genetic algorithms and attempts to learn its opponent's preferences according to the history of the counter-offers based upon stochastic approximation. We also consider two types of agents: level-0 agents are only concerned with their own interest while level-1 agents consider also their opponents' utility. Our goal is to develop an automated negotiator that guides the negotiation process so as to maximize both parties' payoff.

Original languageEnglish
Pages (from-to)195-204
Number of pages10
JournalComputer Networks
Volume37
Issue number2
DOIs
Publication statusPublished - Oct 2001

Scopus Subject Areas

  • Computer Networks and Communications

User-Defined Keywords

  • Genetic algorithms
  • Intelligent agents
  • Negotiation

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