An Adaptive Multi-Agent Model for Automated Negotiation

被引：3

作者：

Radu, Serban ^{[1
]}

Lungu, Valentin ^{[1
]}

机构：

[1] Univ Politehn Bucuresti, Dept Comp Sci, Bucharest, Romania

来源：

19TH INTERNATIONAL CONFERENCE ON CONTROL SYSTEMS AND COMPUTER SCIENCE (CSCS 2013) | 2013年

关键词：

multi-agent system; automated negotiation; reinforcement learning;

D O I：

10.1109/CSCS.2013.76

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The paper presents a model of heuristic negotiation between self-interested agents, which allows negotiation over multiple issues and learns the agent's negotiation strategy. The agents are using different strategies to negotiate and several models to adjust their decision during negotiation. They are capable of increasing their performance with the experience, by adapting to the environment conditions. The agents' performance, using multiple tactics, is compared to the agents having learning capabilities, based on reinforcement learning techniques. Several tests are performed, in a scenario similar to the TAC-SCM environment.

引用

页码：167 / 174

页数：8

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