Nonlinear two-player zero-sum game approximate solution using a Policy Iteration algorithm
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[1] Paul J. Werbos,et al. Approximate dynamic programming for real-time control and neural modeling , 1992 .
[2] Donald E. Kirk,et al. Optimal control theory : an introduction , 1970 .
[3] T. Başar,et al. Dynamic Noncooperative Game Theory , 1982 .
[4] Frank L. Lewis,et al. Neuro-Fuzzy Control of Industrial Systems with Actuator Nonlinearities , 1987 .
[5] Randal W. Beard,et al. Galerkin approximations of the generalized Hamilton-Jacobi-Bellman equation , 1997, Autom..
[6] Tamer Başar,et al. H1-Optimal Control and Related Minimax Design Problems , 1995 .
[7] Marcus Johnson,et al. A model-free robust policy iteration algorithm for optimal control of nonlinear systems , 2010, 49th IEEE Conference on Decision and Control (CDC).
[8] Frank L. Lewis,et al. Discrete-Time Nonlinear HJB Solution Using Approximate Dynamic Programming: Convergence Proof , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[9] John N. Tsitsiklis,et al. Neuro-Dynamic Programming , 1996, Encyclopedia of Machine Learning.
[10] Richard S. Sutton,et al. Reinforcement Learning is Direct Adaptive Optimal Control , 1992, 1991 American Control Conference.
[11] Frank L. Lewis,et al. 2009 Special Issue: Neural network approach to continuous-time direct adaptive optimal control for partially unknown nonlinear systems , 2009 .
[12] F. Lewis,et al. Model-free Q-learning designs for discrete-time zero-sum games with application to H-infinity control , 2007, 2007 European Control Conference (ECC).
[13] Victor M. Becerra,et al. Optimal control , 2008, Scholarpedia.
[14] S. N. Balakrishnan,et al. Adaptive-critic based neural networks for aircraft optimal control , 1996 .
[15] Donald A. Sofge,et al. Handbook of Intelligent Control: Neural, Fuzzy, and Adaptive Approaches , 1992 .
[16] Weiping Li,et al. Applied Nonlinear Control , 1991 .
[17] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[18] Frank L. Lewis,et al. Nearly optimal control laws for nonlinear systems with saturating actuators using a neural network HJB approach , 2005, Autom..
[19] A. Schaft. L/sub 2/-gain analysis of nonlinear systems and nonlinear state-feedback H/sub infinity / control , 1992 .
[20] Frank L. Lewis,et al. Adaptive critic neural network for feedforward compensation , 1999, Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251).
[21] George G. Lendaris,et al. Adaptive critic design for intelligent steering and speed control of a 2-axle vehicle , 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.
[22] Frank L. Lewis,et al. Model-free Q-learning designs for linear discrete-time zero-sum games with application to H-infinity control , 2007, Autom..
[23] J J Hopfield,et al. Neurons with graded response have collective computational properties like those of two-state neurons. , 1984, Proceedings of the National Academy of Sciences of the United States of America.
[24] Frank L. Lewis,et al. Online Synchronous Policy Iteration Method for Optimal Control , 2009 .
[25] S. N. Balakrishnan,et al. State-constrained agile missile control with adaptive-critic-based neural networks , 2002, IEEE Trans. Control. Syst. Technol..
[26] Kenji Doya,et al. Reinforcement Learning in Continuous Time and Space , 2000, Neural Computation.
[27] George G. Lendaris,et al. Adaptive dynamic programming , 2002, IEEE Trans. Syst. Man Cybern. Part C.
[28] Alexander S. Poznyak,et al. Differential Neural Networks for Robust Nonlinear Control: Identification, State Estimation and Trajectory Tracking , 2001 .
[29] G. Lewicki,et al. Approximation by Superpositions of a Sigmoidal Function , 2003 .
[30] Robert F. Stengel,et al. An adaptive critic global controller , 2002, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301).
[31] Stef Tijs,et al. Introduction to Game Theory , 2003 .
[32] F. L. Lewis. NONLINEAR NETWORK STRUCTURES FOR FEEDBACK CONTROL , 1999 .
[33] Richard S. Sutton,et al. Neuronlike adaptive elements that can solve difficult learning control problems , 1983, IEEE Transactions on Systems, Man, and Cybernetics.
[34] Richard S. Sutton,et al. Learning to predict by the methods of temporal differences , 1988, Machine Learning.