An adaptive genetic algorithm and its application in bilateral multi-issue negotiation

Abstract In multi-agent based E-commerce, how to make the negotiation agents gain satisfying result farthest and negotiate efficiently is a key issue. As for this problem, an adaptive genetic algorithm is presented and the algorithm is applied in bilateral multi-issue simultaneous bidding negotiation. In the system, agents can send their information including issue • issue weight • issue reservation price etc to a third party agent, and the third party agent then uses the adaptive genetic algorithm to give the optimal solution. In the experiments, the two methods are used to compare. One is the simple genetic algorithm (SGA); the second is the adaptive genetic algorithm (AGA). The SGA uses 218 runs to gain the satisfying result, while the AGA only uses 152 runs to gain the satisfying result. The experiments' results show that agents with AGA can negotiation more efficiently than SGA in multi-agent based e-commerce.

[1]  Katia P. Sycara,et al.  Bayesian learning in negotiation , 1998, Int. J. Hum. Comput. Stud..

[2]  M. Lynne Markus,et al.  Electronic marketplaces in Hong Kong's trading industry , 2002, Proceedings of the 35th Annual Hawaii International Conference on System Sciences.

[3]  Von-Wun Soo,et al.  On-line incremental learning in bilateral multi-issue negotiation , 2002, AAMAS '02.

[4]  Enrico Gerding,et al.  Multi-Issue Negotiation Processes by Evolutionary Simulation, Validation and Social Extensions , 2003 .

[5]  Thomas Bäck,et al.  Evolutionary Algorithms in Theory and Practice , 1996 .

[6]  Ken Binmore,et al.  Applying game theory to automated negotiation , 1999 .

[7]  Nicholas R. Jennings,et al.  Determining successful negotiation strategies: an evolutionary approach , 1998, Proceedings International Conference on Multi Agent Systems (Cat. No.98EX160).

[8]  Michael J. Prietula,et al.  Getting to best: efficiency versus optimality in negotiation , 2000, Cogn. Sci..

[9]  Stuart I. Feldman,et al.  E-Business: Electronic Marketplaces , 2000, IEEE Internet Comput..

[10]  Herbert Dawid,et al.  Adaptive Learning by Genetic Algorithms, Analytical Results and Applications to Economic Models, 2nd extended and revised edition , 1999 .

[11]  Christopher P. Holland,et al.  Competition and strategy in electronic marketplaces , 2002, Proceedings of the 35th Annual Hawaii International Conference on System Sciences.

[12]  Arnold Kamis,et al.  Electronic Marketing , 2007, 2007 40th Annual Hawaii International Conference on System Sciences (HICSS'07).

[13]  Athanasia Pouloudi,et al.  Using intelligent agents for knowledge management in e-commerce , 2002, ITI 2002. Proceedings of the 24th International Conference on Information Technology Interfaces (IEEE Cat. No.02EX534).