N. Abbeel, A. Peter-abbeel, and . Ng, Apprenticeship learning via inverse reinforcement learning, Twenty-first international conference on Machine learning , ICML '04, 2004.
DOI : 10.1145/1015330.1015430

. Archibald, On the generation of markov decision processes, Journal of the Operational Research Society, pp.354-361, 1995.

A. Bagnell and S. Ross, Efficient Reductions for Imitation Learning, Proceedings of the 13th International Conference on Artificial Intelligence and Statistics, pp.661-668, 2010.

T. Bertsekas, P. Dimitri, . Bertsekas, N. John, and . Tsitsiklis, Neuro-Dynamic Programming, Athena Scientific, 1996.

. Bhatnagar, Natural actor???critic algorithms, Automatica, vol.45, issue.11, pp.452471-2482, 2009.
DOI : 10.1016/j.automatica.2009.07.008
URL : https://hal.archives-ouvertes.fr/hal-00840470

C. , L. Chang, and C. , LIBSVM: A library for support vector machines Software available at http: //www Nonparametric bayesian policy priors for reinforcement learning Regularized policy iteration, Advances in Neural Information Processing Systems Shie Mannor, and Csaba Szepesvári Advances in Neural Information Processing Systems, pp.27-28, 2009.

. Grant, . Boyd, S. Grant, and . Boyd, CVX: Matlab software for disciplined convex programming , version 2.1, 2014.

L. Kakade, J. Kakade, and . Langford, Approximately optimal approximate reinforcement learning, Proceedings of the Nineteenth International Conference on Machine Learning, ICML '02, pp.267-274, 2002.

. Kim, Learning from limited demonstrations Reinforcement learning as classification: Leveraging modern classifiers, Advances in Neural Information Processing Systems ICML, pp.2859-2867, 2003.

. Lazaric, Analysis of a classification-based policy iteration algorithm Error bounds for approximate policy iteration, ICML- 27th International Conference on Machine Learning International Conference on Machine Learning, pp.607-614, 2003.

R. Ng, S. Ng, and . Russell, Algorithms for inverse reinforcement learning, Proceedings of the 17th International Conference on Machine Learning, pp.663-670, 2000.

. Piot, Boosted Bellman Residual Minimization Handling Expert Demonstrations, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD, 2014.
DOI : 10.1007/978-3-662-44851-9_35
URL : https://hal.archives-ouvertes.fr/hal-01060953

B. Ross, S. Ross, and J. Bagnell, Reinforcement and imitation learning via interactive no-regret learning, 2014.