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Erschienen in:
1997 | OriginalPaper | Buchkapitel
Reinforcement Learning in the Multi-Robot Domain
verfasst von : Maja J. Matarić
Erschienen in: Robot Colonies
Verlag: Springer US
Enthalten in: Professional Book Archive
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This paper describes a formulation of reinforcement learning that enables learning in noisy, dynamic environments such as in the complex concurrent multi-robot learning domain. The methodology involves minimizing the learning space through the use of behaviors and conditions, and dealing with the credit assignment problem through shaped reinforcement in the form of heterogeneous reinforcement functions and progress estimators. We experimentally validate the approach on a group of four mobile robots learning a foraging task.