B. M. Veloso-m, Convergence and no-regret in multiagent learning, Proceedings of the Eighteenth International Conference on Machine Learning, pp.27-34, 2001.

B. M. Veloso-m, Rational and convergent learning in stochastic games, Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, pp.1021-1026, 2001.

C. Y. Kaelbling-l, Playing is believing: the role of beliefs in multi-agent learning, Advances in Neural Information Processing Systems 14, 2001.

C. C. Boutilier-c, The dynamics of reinforcement learing in cooperative multiagent systems, Proceedings of the Fifteenth National Conference on Artificial Intelligence, 1998.

G. A. Hall-k, Correlated-q learning, Proceedings of the Twentieth International Conference on Machine Learning (ICML), 2003.

H. S. Mas-colell, A simple adaptive procedure leading to correlated equilibrium, Econometrica, vol.68, issue.5, pp.1127-1150, 2000.

H. J. Wellman-m, Nash q-learning for general-sum stochastic games, Journal of Machine Learning Research, 2003.

L. M. Stone-p, Leading best-response stratgies in repeated games, 2001.

N. J. Zame-w, Non-computable strategies and discounted repeated games, Economic Theory, 1996.

O. M. Rubinstein-a, A course in game theory, 1994.

S. S. Kearns-m and . Mansour-y, Nash convergence of gradient dynamics in general-sum games, Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence, 2000.