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http://hdl.handle.net/1942/14344| Title: | Multiagent Learning: Basics, Challenges, and Prospects | Authors: | TUYLS, Karl Weiss, Gerhard |
Issue Date: | 2012 | Publisher: | AMER ASSOC ARTIFICIAL INTELL | Source: | AI MAGAZINE, 33 (3), p. 41-52 | 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 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. | Notes: | [Tuyls, Karl] Maastricht Univ, Dept Knowledge Engn, Res Grp Swarm Robot & Learning Multiagent Syst, Maastricht Swarmlab, Maastricht, Netherlands. [Tuyls, Karl] Vrije Univ Brussel, Brussels, Belgium. [Tuyls, Karl] Hasselt Univ, Hasselt, Belgium. [Tuyls, Karl] Eindhoven Univ Technol, NL-5600 MB Eindhoven, Netherlands. [Weiss, Gerhard] Software Competence Ctr Hagenberg GmbH, Hagenberg, Austria. [Weiss, Gerhard] Tech Univ Munich, Dept Comp Sci, D-8000 Munich, Germany. [Weiss, Gerhard] Maastricht Univ, Dept Knowledge Engn, Fac Humanities & Sci, Maastricht, Netherlands. | Keywords: | Computer Science, Artificial Intelligence | Document URI: | http://hdl.handle.net/1942/14344 | ISSN: | 0738-4602 | e-ISSN: | 2371-9621 | ISI #: | 000309621600004 | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2013 |
| Appears in Collections: | Research publications |
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