G. Boone, Minimum-time control of the Acrobot, Proceedings of International Conference on Robotics and Automation, pp.3281-3287, 1997.
DOI : 10.1109/ROBOT.1997.606789

R. Coulom, Reinforcement Learning Using Neural Networks, with Applications to Motor Control, 2002.
URL : https://hal.archives-ouvertes.fr/tel-00003985

K. Doya, Reinforcement Learning in Continuous Time and Space, Neural Computation, vol.3, issue.1, pp.243-269, 2000.
DOI : 10.1109/9.580874

Y. Le-cun, L. Bottou, G. B. Orr, and K. Müller, Efficient BackProp, Neural Networks: Tricks of the Trade, 1998.

J. L. Mcclelland, B. L. Mcnaughton, and R. C. Reilly, Why there are complementary learning systems in the hippocampus and neocortex: Insights from the successes and failures of connectionist models of learning and memory., Psychological Review, vol.102, issue.3, pp.419-457, 1995.
DOI : 10.1037/0033-295X.102.3.419

R. Munos and A. Moore, Variable resolution discretization for high-accuracy solutions of optimal control problems, International Joint Conference on Artificial Intelligence, 1999.

M. Spong, The swing up control problem for the Acrobot, IEEE Control Systems Magazine, vol.15, issue.1, pp.49-55, 1995.
DOI : 10.1109/37.341864

R. S. Sutton, Generalization in reinforcement learning: Successful examples using sparse coarse coding, Advances in Neural Information Processing Systems, pp.1038-1044, 1996.

S. Richard, A. G. Sutton, and . Barto, Reinforcement Learning: An Introduction, 1998.

J. Yoshimoto, S. Ishii, and M. Sato, Application of reinforcement learning to balancing of Acrobot, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028), pp.516-521, 1999.
DOI : 10.1109/ICSMC.1999.815605