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Using Learning Automata in Coordination Among Heterogeneous Agents in a Complex Multi-Agent Domain
Mohammadreza Khojasteh, Aida Kazimi
Pages - 39 - 59     |    Revised - 15-05-2012     |    Published - 20-06-2012
Volume - 3   Issue - 3    |    Publication Date - June 2012  Table of Contents
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KEYWORDS
Distributed Artificial Intelligence, Learning Automata, Coordination, Heterogeneous Agents, RoboCup Rescue Simulation
ABSTRACT
This paper describes our use of Learning Automata as a reinforcement learning method in coordination among three heterogeneous teams of agents acting in RoboCup Rescue Simulation environment. We provide a brief introduction to Learning Automata and Cellular Learning Automata, the reinforcement machine learning methods that we have used in lots of parts of our agents’ development. Then we will describe the major challenges each team of agents should be concerned about in such a complex domain and for each challenge, we propose our approaches to develop cooperative teams. Finally, some results of using Learning Automata in coordinating these heterogeneous teams of agents that cooperate to mitigate the disastrous damages in a simulated city are evaluated.
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Mr. Mohammadreza Khojasteh
Department of Computer Engineering, Shiraz Branch, Islamic Azad University - Iran
khojasteh@iaushiraz.ac.ir
Mr. Aida Kazimi
Department of Computer Engineering, Shiraz Branch, Islamic Azad University - Iran


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