Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3 (AAMAS'04) New York City, New York, USA July 19-July 23 ISBN: 0-7695-2092-8
This paper presents a reinforcement learning algorithm used to allocate tasks to agents in an uncertain real-time environment. In such environment, tasks have to be analyzed and allocated really fast for the multiagent system to be effective. To analyze those tasks, described by a lot of attributes, we have used a selective perception technique to enable agents to narrow down the description of each task, enabling the reinforcement learning algorithm to work on a problem with a reasonable number of possible states.
Citation:
Sébastien Paquet, Nicolas Bernier, Brahim Chaib-draa, "From Global Selective Perception to Local Selective Perception," aamas, vol. 3, pp.1352-1353, Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3 (AAMAS'04), 2004 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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