"Reinforcement Learning for Optimal Feedback Control: A Lyapunov-Based Approach"

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Book	Author(s)	Year	Publisher
Reinforcement Learning for Optimal Feedback Control: A Lyapunov-Based Approach	Rushikesh Kamalapurkar; Patrick Walters; Joel Rosenfeld; Warren Dixon	1st ed. 2018	Springer International Publishing
Deep Reinforcement Learning with Guaranteed Performance: A Lyapunov-Based Approach	Yinyan Zhang; Shuai Li; Xuefeng Zhou	1st ed. 2020	Springer International Publishing
Reinforcement learning and optimal control /	Bertsekas, Dimitri P.,		Athena Scientific
Reinforcement Learning and Approximate Dynamic Programming for Feedback Control	Frank L. Lewis; Derong Liu	2013	Wiley-IEEE Press
Reinforcement learning and Optimal Control - Draft version	Dmitri Bertsekas	2019	Athena Scientific
Optimal Feedback Control	Rafail Gabasov; Faima M. Kirillova; Svetlana V. Prischepova	1995	Springer Berlin Heidelberg
Nonlinear Control of Engineering Systems: A Lyapunov-Based Approach	Warren E. Dixon; Aman Behal; Darren M. Dawson; Siddharth P. Nagarkatti	2003	Birkhäuser Boston
Nonlinear Dynamical Systems and Control: A Lyapunov-Based Approach	Wassim M. Haddad; VijaySekhar Chellaboina	2008	Princeton University Press
Reinforcement Learning Aided Performance Optimization of Feedback Control Systems	Changsheng Hua	1st ed. 2021	Springer Fachmedien Wiesbaden
Design of Optimal Feedback for Structural Control	Ido Halperin; Grigory Agranovich; Yuri Ribakov	2021	Routledge
Optimal Adaptive Control and Differential Games by Reinforcement Learning Principles	Draguna Vrabie, Kyriakos G. Vamvoudakis, Frank. L Lewis	2013	The Institution of Engineering and Technology
Geometry of feedback and optimal control /	Jakubczyk, Bronisław.; Respondek, W.	[1998], ©1998.	Marcel Dekker,
Lyapunov-Based Control of Mechanical Systems	Marcio S. de Queiroz; Darren M. Dawson; Siddharth P. Nagarkatti; Fumin Zhang	2000	Birkhäuser Boston
Lyapunov-Based Control of Robotic Systems	Aman Behal; Warren Dixon; Darren M. Dawson; Bin Xian	2010	Routledge
Control Systems and Reinforcement Learning	Sean Meyn	2022-06	Cambridge University Press
Multi-Agent Coordination: A Reinforcement Learning Approach	Arup Kumar Sadhu; Amit Konar	2021	Wiley-IEEE Press
Multi-Agent Machine Learning: A Reinforcement Approach	Howard M. Schwartz	2014	John Wiley & Sons
Nonlinear Systems Stability Analysis: Lyapunov-Based Approach	Seyed Kamaleddin Yadavar Nikravesh	2013	Routledge
Handbook of Reinforcement Learning and Control	Kyriakos G. Vamvoudakis; Yan Wan; Frank L. Lewis; Derya Cansever	1st ed. 2021	Springer International Publishing
A Relaxation-Based Approach to Optimal Control of Hybrid and Switched Systems	Vadim Azhmyakov	2019	Butterworth-Heinemann
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Chapter	Author(s)	Book	Book Authors	Year	Publisher
Lyapunov-Based Reinforcement Learning for Decentralized Multi-agent Control	Qingrui Zhang; Hao Dong; Wei Pan	Distributed Artificial Intelligence: Second International Conference, DAI 2020, Nanjing, China, October 24–27, 2020, Proceedings	Matthew E. Taylor; Yang Yu; Edith Elkind; Yang Gao	1st ed. 2020	Springer International Publishing
Model-Based Reinforcement Learning for Approximate Optimal Control	Rushikesh Kamalapurkar; Patrick Walters; Joel Rosenfeld; Warren Dixon	Reinforcement Learning for Optimal Feedback Control: A Lyapunov-Based Approach	Rushikesh Kamalapurkar; Patrick Walters; Joel Rosenfeld; Warren Dixon	1st ed. 2018	Springer International Publishing
Reinforcement Learning for Approximate Optimal Control	Warren E. Dixon	Encyclopedia of Systems and Control	John Baillieul; Tariq Samad	2nd ed. 2021	Springer International Publishing
Reinforcement Learning for Approximate Optimal Control	Warren E. Dixon	Encyclopedia of Systems and Control	John Baillieul; Tariq Samad	0th ed. 2020	Springer London
A Model-Based Reinforcement Learning Approach to Time-Optimal Control Problems	Hsuan-Cheng Liao; Jing-Sin Liu	Advances and Trends in Artificial Intelligence. From Theory to Practice: 32nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2019, Graz, Austria, July 9–11, 2019, Proceedings	Franz Wotawa; Gerhard Friedrich; Ingo Pill; Roxane Koitz-Hristov; Moonis Ali	1st ed. 2019	Springer International Publishing
Reinforcement Learning and Feedback Control	Changsheng Hua	Reinforcement Learning Aided Performance Optimization of Feedback Control Systems	Changsheng Hua	1st ed. 2021	Springer Fachmedien Wiesbaden
A Reinforcement Learning Approach to On-Line Optimal Control	P.E. An; S. Aslam-Mir; M. Brown; C.J. Harris	World Congress On Neural Networks-San Diego: 1994 International Neural Network Society Annual Meeting	Paul Werbos; Harold Szu; Bernard Widrow	1994	Routledge
Deep Reinforcement Learning for Optimal Traffic Control	Rajasekhar Nannapaneni; Raghavendra V. Kulkarni; Shalabh Bhatnagar	Machine Intelligence and Smart Systems: Proceedings of MISS 2021	Shikha Agrawal; Kamlesh Kumar Gupta; Jonathan H. Chan; Jitendra Agrawal; Manish Gupta	1st ed. 2022	Springer Nature Singapore
Online Adaptive Optimal Control Based on Reinforcement Learning	Draguna Vrabie; Frank Lewis	Optimization and Optimal Control: Theory and Applications	Altannar Chinchuluun; Panos M. Pardalos; Rentsen Enkhbat; Ider Tseveendorj	2010	Springer New York
Development of Conceptual Framework for Reinforcement Learning Based Optimal Control	Smriti Gupta; Sabita Pal; Kundan Kumar; Kuntal Ghosh	Innovation in Electrical Power Engineering, Communication, and Computing Technology: Proceedings of Second IEPCCT 2021	Manohar Mishra; Renu Sharma; Akshay Kumar Rathore; Janmenjoy Nayak; Bighnaraj Naik	1st ed. 2022	Springer Nature Singapore
Optimal Control and Reinforcement Learning for Robot: A Survey	Haodong Feng; Lei Yu; Yuqing Chen	Collaborative Computing: Networking, Applications and Worksharing: 17th EAI International Conference, CollaborateCom 2021, Virtual Event, October 16-18, 2021, Proceedings, Part I	Honghao Gao; Xinheng Wang	1st ed. 2021	Springer International Publishing
Reinforcement Learning Informed by Optimal Control	Magnus Önnheim; Pontus Andersson; Emil Gustavsson; Mats Jirstrand	Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions: 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings	Igor V. Tetko; Věra Kůrková; Pavel Karpov; Fabian Theis	1st ed. 2019	Springer International Publishing
REINFORCEMENT LEARNING AND OPTIMAL ADAPTIVE CONTROL		Optimal Control, 3rd Edition	Frank L. Lewis	2012	John Wiley & Sons
Stick-Slip Control: Lyapunov-Based Approach	Martha Belem Saldivar Márquez; Islam Boussaada; Hugues Mounier; Silviu-Iulian Niculescu	Analysis and Control of Oilwell Drilling Vibrations: A Time-Delay Systems Approach	Martha Belem Saldivar Márquez; Islam Boussaada; Hugues Mounier; Silviu-Iulian Niculescu	2015	Springer International Publishing
Reinforcement Learning for Control		Human-Robot Interaction Control Using Reinforcement Learning	Wen Yu; Adolfo Perrusquia	2022	Wiley-IEEE Press
Optimal feedback control	Arthur E. Bryson; Yu-Chi Ho	Applied Optimal Control: Optimization, Estimation, and Control	A. E. Bryson	1975	Routledge
Optimal Feedback Control	Asen L. Dontchev	Lectures on Variational Analysis	Asen L. Dontchev	1st ed. 2021	Springer International Publishing
Optimal Feedback Control		Biological Learning and Control: How the Brain Builds Representations, Predicts Events, and Makes Decisions	Reza Shadmehr; Sandro Mussa-Ivaldi	2012	The MIT Press
Optimal feedback control		Elements of optimal control	Stephen J. Citron	1969	Holt, Rinehart and Winston
Optimal feedback control		Applied optimal control: optimization, estimation, and control	Arthur E. Bryson, Yu-Chi Ho	1969	Blaisdell Pub. Co.
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