Multiagent Learning: Basics, Challenges, and Prospects

Authors

  • Karl Tuyls Maastricht University
  • Gerhard Weiss Maastricht University

DOI:

https://doi.org/10.1609/aimag.v33i3.2426

Abstract

Multiagent systems (MAS) are widely accepted as an important method for solving problems of a distributed nature. A key to the success of MAS is efficient and effective multiagent learning (MAL). The past twenty-five years have seen a great interest and tremendous progress in the field of MAL. This article introduces and overviews this field by presenting its fundamentals, sketching its historical development and describing some key algorithms for MAL. Moreover, main challenges that the field is facing today are indentified.

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Published

2012-09-20

How to Cite

Tuyls, K., & Weiss, G. (2012). Multiagent Learning: Basics, Challenges, and Prospects. AI Magazine, 33(3), 41. https://doi.org/10.1609/aimag.v33i3.2426

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Section

Articles