Autonomous Robots

, Volume 4, Issue 1, pp 73–83

Reinforcement Learning in the Multi-Robot Domain

  • Maja J. Matarić

DOI: 10.1023/A:1008819414322

Cite this article as:
Matarić, M.J. Autonomous Robots (1997) 4: 73. doi:10.1023/A:1008819414322


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 

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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