Predicting and Preventing Coordination Problems in Cooperative Q-learning Systems

Fulda, Nancy; Ventura, Dan

Predicting and Preventing Coordination Problems in Cooperative Q-learning Systems

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Proceedings of the Twentieth International Joint Conference on Artificial Intelligence. Pages 780-784.

Abstract

We present a conceptual framework for creating Q-learning-based algorithms that converge to optimal equilibria in cooperative multiagent settings. This framework includes a set of conditions that are sufficient to guarantee optimal system performance. We demonstrate the efficacy of the framework by using it to analyze several well-known multi-agent learning algorithms and conclude by employing it as a design tool to construct a simple, novel multiagent learning algorithm.

Nancy Fulda, and Dan Ventura. 2007. Predicting and Preventing Coordination Problems in Cooperative Q-learning Systems. In Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, IJCAI-07. IJCAI, 780–784. https://ijcai.org/proceedings/2007/125

@inproceedings{ijcai2007p125,
  title     = {Predicting and Preventing Coordination Problems in Cooperative Q-learning Systems},
  author    = {Fulda, Nancy and Ventura, Dan},
  booktitle = {Proceedings of the Twentieth International Joint Conference on
               Artificial Intelligence, {IJCAI-07}},
  publisher = {International Joint Conferences on Artificial Intelligence},
  editor    = {Ramon López de Mántaras},
  pages     = {780--784},
  year      = {2007},
  url       = {https://ijcai.org/proceedings/2007/125},
}

TY  - CPAPER
TI  - Predicting and Preventing Coordination Problems in Cooperative Q-learning Systems
AU  - Fulda, Nancy
AU  - Ventura, Dan
T2  - Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, IJCAI-07
PB  - International Joint Conferences on Artificial Intelligence
PY  - 2007
SP  - 780
EP  - 784
UR  - https://ijcai.org/proceedings/2007/125
ER  -