Multi-Issue Negotiation Research Based On Niched Co-evolutionary Genetic Algorithm

Author

Yuan Yong ; Liang Yong-Quan

Author_Institution

Shandong Univ. of Sci. & Technol., Qingdao

Volume

1

fYear

2007

Firstpage

564

Lastpage

569

Abstract

This paper presents a simulation algorithm called SANCGA for bilateral multi-issue negotiation based on co-evolutionary genetic algorithm and isolated niche technique, and designs an experiment to simulate the co-evolutionary strategy learning process in an alternating offer negotiation scenario. The experiment results validate that SANCGA algorithm can form local niches in the strategy populations and generate an approximate Pareto optimal strategy set.

Keywords

Pareto optimisation; genetic algorithms; learning (artificial intelligence); multi-agent systems; set theory; Pareto optimal strategy set; SANCGA simulation algorithm; bilateral multiissue negotiation; coevolutionary genetic algorithm; coevolutionary strategy learning process; isolated niche technique; multiagent system; Artificial intelligence; Computational modeling; Context modeling; Distributed computing; Educational institutions; Evolutionary computation; Genetic algorithms; Genetic engineering; Information science; Software engineering;

fLanguage

English

Publisher

ieee

Conference_Titel

Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2007. SNPD 2007. Eighth ACIS International Conference on

Print_ISBN

978-0-7695-2909-7

Type

conf

DOI

10.1109/SNPD.2007.433

Filename

4287571