An automated negotiation mechanism based on co-evolution and game theory

An automated negotiation mechanism based on co-evolution and game theory An Automated Negotiation Mechanism Based on CoEvolution and Game Theory Kuo-Ming Chao Nick Godwin Colin Reeves DKERG DKERG SORG School of MIS, School of MIS, School of MIS CoventryUniversity, Coventry University, Coventry University, Coventry UK UK UK University, UK (44) 24 7688 7790 (44) 24 7688 8908 (44) 24 7688 8908 (44) 24 7688 7790 j.chen@ k.chao@ a.n.godwin@ c.reeves@ coventry.ac.uk coventry.ac.uk coventry.ac.uk coventry.ac.uk Jen-Hsiang Chen DKERG School of MIS, Peter Smith School of Computing and Engineering Sunderland University, UK (44) 191 515 2761 peter.smith@ sunderland.ac.uk Abstract The problems associated with current automated negotiation approaches are of little feasibility in practical industry applications. This paper describes a new method that combines a game theory approach and a co-evolutionary approach to support an effective negotiation model for agents to resolve conflict. Under this proposed method, the agents without knowing the other agent's strategies and payoffs, produce an optimised resolution that complies Nash equilibrium and Pareto efficiency concepts. We use a finitely repeated prisoner's dilemma game to demonslrate the proposed method. Keywords Game theory, Genetic Algorithm, Prisoner Dilemma, No Fear of Deviation. Introduction Automated negotiation is an important mechanism in multiple agents system, because agents are autonomous, proactive, and self-interested, they http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

An automated negotiation mechanism based on co-evolution and game theory

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Copyright
Copyright © 2002 by ACM Inc.
ISBN
1-58113-445-2
D.O.I.
10.1145/508791.508805
Publisher site
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Abstract

An Automated Negotiation Mechanism Based on CoEvolution and Game Theory Kuo-Ming Chao Nick Godwin Colin Reeves DKERG DKERG SORG School of MIS, School of MIS, School of MIS CoventryUniversity, Coventry University, Coventry University, Coventry UK UK UK University, UK (44) 24 7688 7790 (44) 24 7688 8908 (44) 24 7688 8908 (44) 24 7688 7790 j.chen@ k.chao@ a.n.godwin@ c.reeves@ coventry.ac.uk coventry.ac.uk coventry.ac.uk coventry.ac.uk Jen-Hsiang Chen DKERG School of MIS, Peter Smith School of Computing and Engineering Sunderland University, UK (44) 191 515 2761 peter.smith@ sunderland.ac.uk Abstract The problems associated with current automated negotiation approaches are of little feasibility in practical industry applications. This paper describes a new method that combines a game theory approach and a co-evolutionary approach to support an effective negotiation model for agents to resolve conflict. Under this proposed method, the agents without knowing the other agent's strategies and payoffs, produce an optimised resolution that complies Nash equilibrium and Pareto efficiency concepts. We use a finitely repeated prisoner's dilemma game to demonslrate the proposed method. Keywords Game theory, Genetic Algorithm, Prisoner Dilemma, No Fear of Deviation. Introduction Automated negotiation is an important mechanism in multiple agents system, because agents are autonomous, proactive, and self-interested, they

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