A General Convergence Method for Reinforcement Learning in the Continuous Case
暂无分享,去创建一个
[1] G. Barles,et al. Convergence of approximation schemes for fully nonlinear second order equations , 1990, 29th IEEE Conference on Decision and Control.
[2] W. Fleming,et al. Controlled Markov processes and viscosity solutions , 1992 .
[3] G. Barles. Solutions de viscosité des équations de Hamilton-Jacobi , 1994 .
[4] Tyrone E. Duncan,et al. Numerical Methods for Stochastic Control Problems in Continuous Time (Harold J. Kushner and Paul G. Dupuis) , 1994, SIAM Rev..
[5] Andrew G. Barto,et al. Learning to Act Using Real-Time Dynamic Programming , 1995, Artif. Intell..
[6] Rémi Munos,et al. A Convergent Reinforcement Learning Algorithm in the Continuous Case: The Finite-Element Reinforcement Learning , 1996, ICML.
[7] Stanley J. Rosenschein,et al. Learning to act using real-time dynamic programming , 1996 .
[8] Rémi Munos,et al. Reinforcement Learning for Continuous Stochastic Control Problems , 1997, NIPS.
[9] Rémi Munos,et al. A Convergent Reinforcement Learning Algorithm in the Continuous Case Based on a Finite Difference Method , 1997, IJCAI.
[10] H. Kushner. Numerical Methods for Stochastic Control Problems in Continuous Time , 2000 .