Multiagent Learning: Basics, Challenges, and Prospects

Karl Tuyls*, Gerhard Weiss

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


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 25 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 identified.
Original languageEnglish
Pages (from-to)41-52
Number of pages13
JournalAi Magazine
Issue number3
Publication statusPublished - 1 Oct 2012

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