Authors:
Jieyu Zhan
1
;
Xudong Luo
1
;
Wenjun Ma
2
and
Youzhi Zhang
1
Affiliations:
1
Sun Yat-sen University, China
;
2
Queen's University Belfast, United Kingdom
Keyword(s):
Game Theory, Fuzzy Logic, Bargaining Game, Preference, Agent.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Computational Intelligence
;
Fuzzy Systems
;
Negotiation and Interaction Protocols
;
Soft Computing
Abstract:
Nowadays, decisions in estate investment are made by a group of investors with different demands and then how to find an agreement among them become an essential issue. Thus, this paper introduces a fuzzy logic based bargaining model to solve such problems. Moreover, we also do lots of simulation experiments to reveal how bargainers’ risk attitude, patience and regret degree influence the outcome of a game, and benchmark our model with the previous one. From these experiments, we can conclude that our model can reflect the human
intuitions well, has a higher success rate, and bargains more efficiently than the previous one.