A genetic agent-based negotiation system

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 g...

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Bibliographic Details
Published in:Computer networks (Amsterdam, Netherlands : 1999) Netherlands : 1999), 2001-10, Vol.37 (2), p.195-204
Main Authors: Choi, Samuel P.M., Liu, Jiming, Chan, Sheung-Ping
Format: Article
Language:English
Subjects:
Algorithms
Automation
Business
Business to business commerce
Computer applications
Electronic commerce
Electronic money
Genetic algorithms
Intelligent agents
Negotiation
Negotiations
Online payment
Stochastic models
Studies
Transactions
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Summary: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.
ISSN:1389-1286
1872-7069
DOI:10.1016/S1389-1286(01)00215-8