Coordination through Mutual Notification in Cooperative Multiagent Reinforcement Learning (2004) [2 citations — 0 self]
by Daniel Szer
In Proceedings of AAMAS 2004
http://www.loria.fr/~szer/publications/aamas2004.ps
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Abstract:
We present a new algorithm for cooperative reinforcement learning in multiagent systems. Our main concern is the correct coordination between the members of the team: We seek to obtain an optimal solution for the team as a whole while keeping the learning as much decentralized as possible. We consider autonomous and independently learning agents that do not store any explicit information about their teammates ’ behavior, as well as possibly different reward functions for each agent. Coordination between agents occurs through communication, namely the mutual notification algorithm. 1.
Citations
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| 95 | The complexity of decentralized control of markov decision processes – Bernstein, Givan, et al. - 2002 |
| 90 | Sequential optimality and coordination in multiagent systems – Boutilier - 1999 |
| 43 | Optimizing information exchange in cooperative multi-agent systems – Goldman, Zilberstein - 2003 |
| 27 | Transition-independent decentralized markov decision processes – Becker, Zilberstein, et al. - 2003 |
| 2 | and François Charpillet. Coordination through mutual notification in cooperative multiagent reinforcement learning – Szer - 2004 |
| 1 | The complexity of decentralized control of markov deAccumulated joint policy value With communication – Bernstein, Zilberstein, et al. |
