Title :
An approach to solving deadlock in multi-issue negotiation
Author :
Qing, Guo ; Chun, Chen
Author_Institution :
Dept. of Comput. Sci., Zhejiang Univ., Hangzhou, China
Abstract :
In multi-issue negotiation among agents, how to resolve negotiation failure induced by deadlock involved with one certain issue is an inviting task. We propose an equivalent replacement mechanism for reservation values of multiple issues in bi-lateral negotiation, which dynamically adjusts reservation values of every issue to solve negotiation deadlock on the premise of guaranteeing the integrated utility of the participants, and give a tactic of equivalent replacement for reservation valued based on reinforcement-learning algorithm, which maximizes the integrated utility of participants and improves the negotiation efficiency.
Keywords :
learning (artificial intelligence); multi-agent systems; bi-lateral negotiation; multiagent system; multiissue agent negotiation; negotiation deadlock; negotiation failure; reinforcement learning; reinforcement-learning algorithm; replacement mechanism; reservation value adjustment; reservation values; Bayesian methods; Computer science; Costs; Game theory; Genetic algorithms; Iterative algorithms; Machine learning algorithms; Multiagent systems; Protocols; System recovery;
Conference_Titel :
Information Reuse and Integration, 2003. IRI 2003. IEEE International Conference on
Print_ISBN :
0-7803-8242-0
DOI :
10.1109/IRI.2003.1251394
