Adaptive agent selection in large-scale multi-agent systems

被引：0
|
作者：
Sugawara, Toshiharu
Fukuda, Kensuke
Hirotsu, Toshio
Sato, Shin-ya
Kurihara, Satoshi
机构：
[1] NTT Corp, Commun Sci Labs, Atsugi, Kanagawa 2430198, Japan
[2] Toyohashi Univ Technol, Toyohashi, Aichi, Japan
[3] NTT Corp, Network Innovat Labs, Atsugi, Kanagawa 2430198, Japan
[4] Osaka Univ, Suita, Osaka 565, Japan
来源：
PRICAI 2006: TRENDS IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS | 2006年 / 4099卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
An agent in a multi-agent system (MAS) has to select appropriate agents to assign tasks. Unfortunately no agent in an open environment can identify the states of all agents, so this selection must be done according to local information about the other known agents; however this information is limited and may contain uncertainty. In this paper we investigate how overall performance of MAS is affected by learning parameters for adaptive strategies to select partner agent for collaboration. We show experimental results using simulation and discuss why overall performance of MAS varies.
引用
收藏
页码：818 / 822
页数：5
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