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A genetic agent-based negotiation system

Authors
Journal
Computer Networks
1389-1286
Publisher
Elsevier
Publication Date
Volume
37
Issue
2
Identifiers
DOI: 10.1016/s1389-1286(01)00215-8
Keywords
  • Negotiation
  • Intelligent Agents
  • Genetic Algorithms
Disciplines
  • Computer Science
  • Mathematics

Abstract

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.

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