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Jan Peters | Debora Clever | Michael Lutter | Boris Belousov | Kim Listmann | Jan Peters | M. Lutter | B. Belousov | K. Listmann | D. Clever
[1] Eugene L. Allgower,et al. Numerical continuation methods - an introduction , 1990, Springer series in computational mathematics.
[2] W. Fleming,et al. Controlled Markov processes and viscosity solutions , 1992 .
[3] S. Lyshevski. Optimal control of nonlinear continuous-time systems: design of bounded controllers via generalized nonquadratic functionals , 1998, Proceedings of the 1998 American Control Conference. ACC (IEEE Cat. No.98CH36207).
[4] Kenji Doya,et al. Reinforcement Learning in Continuous Time and Space , 2000, Neural Computation.
[5] G. Goodwin,et al. Elucidation of the state-space regions wherein model predictive control and anti-windup strategies achieve identical control policies , 2000, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334).
[6] Martin A. Riedmiller. Neural Fitted Q Iteration - First Experiences with a Data Efficient Neural Reinforcement Learning Method , 2005, ECML.
[7] Frank L. Lewis,et al. Nearly optimal control laws for nonlinear systems with saturating actuators using a neural network HJB approach , 2005, Autom..
[8] Stephen P. Boyd,et al. Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.
[9] Yuval Tassa,et al. Least Squares Solutions of the HJB Equation With Neural Network Value-Function Approximators , 2007, IEEE Transactions on Neural Networks.
[10] Jason Weston,et al. Curriculum learning , 2009, ICML '09.
[11] Yuval Tassa,et al. Control-limited differential dynamic programming , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).
[12] ShiNung Ching,et al. Quasilinear Control: Performance Analysis and Design of Feedback Systems with Nonlinear Sensors and Actuators , 2010 .
[13] Zoran Popovic,et al. Discovery of complex behaviors through contact-invariant optimization , 2012, ACM Trans. Graph..
[14] Daniel Liberzon,et al. Calculus of Variations and Optimal Control Theory: A Concise Introduction , 2012 .
[15] Zoran Popovic,et al. Contact-invariant optimization for hand manipulation , 2012, SCA '12.
[16] Sergey Levine,et al. Guided Policy Search , 2013, ICML.
[17] Derong Liu,et al. Neural-Network-Based Online HJB Solution for Optimal Robust Guaranteed Cost Control of Continuous-Time Uncertain Nonlinear Systems , 2014, IEEE Transactions on Cybernetics.
[18] Xiong Yang,et al. Reinforcement learning for adaptive optimal control of unknown continuous-time nonlinear systems with input constraints , 2014, Int. J. Control.
[19] F. Lewis,et al. Online solution of nonquadratic two‐player zero‐sum games arising in the H ∞ control of constrained input systems , 2014 .
[20] Yuval Tassa,et al. Emergence of Locomotion Behaviours in Rich Environments , 2017, ArXiv.
[21] Marc Toussaint,et al. Differentiable Physics and Stable Modes for Tool-Use and Manipulation Planning , 2018, Robotics: Science and Systems.
[22] George E. Karniadakis,et al. Hidden physics models: Machine learning of nonlinear partial differential equations , 2017, J. Comput. Phys..
[23] OpenAI. Learning Dexterous In-Hand Manipulation. , 2018 .
[24] Kim D. Listmann,et al. Deep Lagrangian Networks for end-to-end learning of energy-based control for under-actuated systems , 2019, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[25] Moritz Diehl,et al. CasADi: a software framework for nonlinear optimization and optimal control , 2018, Mathematical Programming Computation.
[26] Jan Peters,et al. Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning , 2019, ICLR.
[27] Jakub W. Pachocki,et al. Learning dexterous in-hand manipulation , 2018, Int. J. Robotics Res..