ApproxRL: A Matlab Toolbox for Approximate RL and DP. This toolbox contains Matlab implementations of a number of approximate reinforcement learning (RL) and dynamic programming (DP) algorithms. Notably, it contains the algorithms used in the numerical examples from the book: L. Busoniu, R. Babuska, B. De Schutter, and D. Ernst, Reinforcement Learning and Dynamic Programming Using Function Approximators, CRC Press, Automation and Control Engineering Series. April 2010, 280 pages, ISBN 978-1439821084.

References in zbMATH (referenced in 31 articles )

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  1. Jung, Tobias; Wehenkel, Louis; Ernst, Damien; Maes, Francis: Optimized look-ahead tree policies: a bridge between look-ahead tree policies and direct policy search (2014)
  2. Laber, Eric B.; Lizotte, Daniel J.; Qian, Min; Pelham, William E.; Murphy, Susan A.: Dynamic treatment regimes: technical challenges and applications (2014)
  3. Lian, Chuanqiang; Xu, Xin; Zuo, Lei; Huang, Zhenhua: Adaptive critic design with graph Laplacian for online learning control of nonlinear systems (2014)
  4. Xu, Xin; Zuo, Lei; Huang, Zhenhua: Reinforcement learning algorithms with function approximation: recent advances and applications (2014)
  5. Fonteneau, Raphael; Murphy, Susan A.; Wehenkel, Louis; Ernst, Damien: Batch mode reinforcement learning based on the synthesis of artificial trajectories (2013)
  6. Jiang, Zhong-Ping; Jiang, Yu: Robust adaptive dynamic programming for linear and nonlinear systems: an overview (2013)
  7. Peters, Markus; Ketter, Wolfgang; Saar-Tsechansky, Maytal; Collins, John: A reinforcement learning approach to autonomous decision-making in smart electricity markets (2013) ioport
  8. Beck, C. L.; Srikant, R.: Error bounds for constant step-size (Q)-learning (2012)
  9. Xu, Hao; Jagannathan, S.; Lewis, F. L.: Stochastic optimal control of unknown linear networked control system in the presence of random delays and packet losses (2012)
  10. Bertsekas, Dimitri P.: Approximate policy iteration: a survey and some new methods (2011)
  11. Powell, Warren B.; Ma, Jun: A review of stochastic algorithms with continuous value function approximation and some new approximate policy iteration algorithms for multidimensional continuous applications (2011)