DocumentCode
1600655
Title
A Fuzzy Bayesian Learning Negotiation Model with Genetic Algorithms
Author
Wu, Yuying ; Lu, Jinxuan ; Yan, Feng
Author_Institution
Beijing Univ. of Technol., Beijing
Volume
5
fYear
2007
Firstpage
379
Lastpage
388
Abstract
An offer is accepted or rejected based on the utility function in the traditional automatic negotiation. Acceptability based on the fuzzy set theory and the membership function is used to evaluate offers. Since different issues have different effect on negotiators, the combined concession in the multi-issue negotiation, Bayesian learning mechanism and genetic algorithm are adopted to update its beliefs about incomplete information. The fuzzy negotiation model is a more practical than the traditional negotiation model.
Keywords
Bayes methods; electronic commerce; fuzzy set theory; genetic algorithms; learning (artificial intelligence); Bayesian learning; electronic commerce; fuzzy negotiation model; fuzzy set theory; genetic algorithm; membership function; utility function; Automatic control; Bayesian methods; Decision making; Economic forecasting; Fuzzy set theory; Genetic algorithms; Internet; Learning systems; Software agents; Technology management;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location
Haikou
Print_ISBN
978-0-7695-2875-5
Type
conf
DOI
10.1109/ICNC.2007.31
Filename
4344870
Link To Document