From Global Selective Perception to Local Selective Perception

Authors:
Sebastien Paquet;Nicolas Bernier;Brahim Chaib-draa
Affiliations:
Laval University;Laval University;Laval University
Venue:
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
Year:
2004

Citing 3
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Abstract

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.