Title :
A negotiation strategy based on uncompromising degree
Author :
An, Bo ; Tang, Lianggui ; Li, Shuangqing ; Cheng, Daijie
Author_Institution :
Coll. of Comput. Sci., Chongqing Univ., China
Abstract :
This work introduces a negotiation strategy based on uncompromising degree. Agents get information of the negotiation opponents in each iteration by means of Bayesian learning mechanism, and then bring forward the proposals for the next iteration according to the negotiation strategy based on uncompromising degree. We analyze Bayesian learning mechanism and use it to get the opponents´ information; introduce the negotiation strategy based on uncompromising degree; discuss how the remaining time affects negotiation strategy. Our strategy regards the whole negotiation process as a dynamic interaction process, which enhances the usage of MAS in complex and dynamic environment. The experiments show that our strategy has good negotiation performance.
Keywords :
belief networks; learning (artificial intelligence); multi-agent systems; negotiation support systems; Bayesian learning; complex environment; dynamic environment; dynamic interaction process; multiagent system; negotiation opponents; negotiation strategy; uncompromising degree; Bayesian methods; Computer science; Density functional theory; Educational institutions; Gaussian distribution; Information analysis; Learning systems; Multiagent systems; Proposals; Random variables;
Conference_Titel :
Intelligent Agent Technology, 2004. (IAT 2004). Proceedings. IEEE/WIC/ACM International Conference on
Print_ISBN :
0-7695-2101-0
DOI :
10.1109/IAT.2004.1342970
