An approach to solving deadlock in multi-issue negotiation

被引：1
|
作者：
Guo, Q [1 ]
Chen, C [1 ]
机构：
[1] Zhejiang Univ, Comp Sci Dept, Hangzhou 310027, Peoples R China
来源：
PROCEEDINGS OF THE 2003 IEEE INTERNATIONAL CONFERENCE ON INFORMATION REUSE AND INTEGRATION | 2003年
关键词：
MAS; negotiation; issue; reinforcement learning;
D O I：
10.1109/IRI.2003.1251394
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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 values based on reinforcement -learning algorithm, which maximizes the integrated utility of participants and improves the negotiation efficiency.
引用
收藏
页码：48 / 52
页数：5
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