Playing is believing: the role of beliefs in multi-agent learning
We propose a new classification for multi-agent learning algorithms, with each league of players characterized by both their possible strategies and possible beliefs. Using this classification, we review the optimality of existing algorithms and discuss some insights that can be gained. We propose a...
| Main Authors: | , |
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| Format: | Article |
| Language: | en_US |
| Published: |
2003
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| Subjects: | |
| Online Access: | http://hdl.handle.net/1721.1/3688 |