Scenario-based Teamworking, how to learn, create, and teach complex plans?

被引：0

作者：

Rad, AA ^{[1
]}

Qaragozlou, N

Zaheri, M

机构：

[1] Amirkabir Univ Technol, Comp Engn Fac, Tehran, Iran

[2] Univ N Carolina, Dept Comp Sci, Charlotte, NC 28223 USA

来源：

ROBOCUP 2003: ROBOT SOCCER WORLD CUP VII | 2004年 / 3020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：

This paper presents the application of a novel method in the multiagent teamwork field called Scenario-based Teamworking (SBT). In SBT method a team of cooperative intelligent agents could be able to execute complex plans in nondeterministic, adversary, and dynamic environments which communication cost is high. The base idea of this method is to define Scenario for different situations. With a graph of scenarios, a team of agents can execute, learn, adapt, and create team plans automatically. This method has implemented in a soccer team of intelligent agents (players and coach) and evaluated in the standard RoboCup simulator environment [1] and results show a significant improvement.

引用

页码：137 / 144

页数：8

共 43 条

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