Abstract
Multi-agent learning is studied for multi-agent environments. Reinforcement learning is used to develop learning algorithms which will help develop agents that will cooperate with other agents in learning how to become experts. This method uses feedback information from agents facilitating information sharing and fuzzy learning.
| Original language | English |
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| Pages | 1363 |
| Number of pages | 1 |
| State | Published - 1996 |
| Event | Proceedings of the 1996 13th National Conference on Artificial Intelligence. Part 2 (of 2) - Portland, OR, USA Duration: 4 Aug 1996 → 8 Aug 1996 |
Conference
| Conference | Proceedings of the 1996 13th National Conference on Artificial Intelligence. Part 2 (of 2) |
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| City | Portland, OR, USA |
| Period | 4/08/96 → 8/08/96 |