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Autonomous Robots

, Volume 4, Issue 1, pp 73–83 | Cite as

Reinforcement Learning in the Multi-Robot Domain

  • Maja J. Matarić
Article

Abstract

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.

robotics robot learning group behavior multi-agent systems reinforcement learning 
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Copyright information

© Kluwer Academic Publishers 1997

Authors and Affiliations

  • Maja J. Matarić
    • 1
  1. 1.Volen Center for Complex Systems, Computer Science DepartmentBrandeis UniversityWaltham

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