A near-optimal polynomial time algorithm for learning in certain classes of stochastic games

Self-Optimizing and Pareto-Optimal Policies in General Environments Based on Bayes-Mixtures

COLT '02 Proceedings of the 15th Annual Conference on Computational Learning Theory

Dispersion games: general definitions and some specific learning results

Eighteenth national conference on Artificial intelligence

R-max - a general polynomial time algorithm for near-optimal reinforcement learning

The Journal of Machine Learning Research

Nash q-learning for general-sum stochastic games

The Journal of Machine Learning Research

Reliability of internal prediction/estimation and its application: I. adaptive action selection reflecting reliability of value function

Neural Networks

Dimensions of complexity of intelligent agents

PCAR '06 Proceedings of the 2006 international symposium on Practical cognitive agents and robots

AWESOME: A general multiagent learning algorithm that converges in self-play and learns a best response against stationary opponents

Machine Learning

Perspectives on multiagent learning

Artificial Intelligence

Solving two-person zero-sum repeated games of incomplete information

Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2

R-MAX: a general polynomial time algorithm for near-optimal reinforcement learning

IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2