Reinforcement Learning for Optimal Feedback Control A Lyapunov-Based Approach /

• Κύριοι συγγραφείς: Kamalapurkar, Rushikesh (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Walters, Patrick (http://id.loc.gov/vocabulary/relators/aut), Rosenfeld, Joel (http://id.loc.gov/vocabulary/relators/aut), Dixon, Warren (http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Έκδοση: 1st ed. 2018.
• Σειρά: Communications and Control Engineering,
• Θέματα: Control engineering.; Calculus of variations.; System theory.; Electrical engineering.; Control and Systems Theory.; Calculus of Variations and Optimal Control; Optimization.; Systems Theory, Control.; Communications Engineering, Networks.

Reinforcement Learning for Optimal Feedback Control develops model-based and data-driven reinforcement learning methods for solving optimal control problems in nonlinear deterministic dynamical systems. In order to achieve learning under uncertainty, data-driven methods for identifying system models...

Πίνακας περιεχομένων:

• Chapter 1. Optimal control
• Chapter 2. Approximate dynamic programming
• Chapter 3. Excitation-based online approximate optimal control
• Chapter 4. Model-based reinforcement learning for approximate optimal control
• Chapter 5. Differential Graphical Games
• Chapter 6. Applications
• Chapter 7. Computational considerations
• Reference
• Index.