Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2021
ISBN 10: 6204732013 ISBN 13: 9786204732015
Librería: preigu, Osnabrück, Alemania
EUR 39,35
Cantidad disponible: 5 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. Fuzzy Reinforcement Learning Based Controller Design | Lyapunov Theory based Reinforcement Learning Controller for Non Linear Systems | Abhishek Kumar | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786204732015 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing Dez 2021, 2021
ISBN 10: 6204732013 ISBN 13: 9786204732015
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 43,90
Cantidad disponible: 2 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book aims at providing basic introduction about reinforcement learning (RL), application of RL as controller and introducing stability in RL. Q-learning is most widely used RL technique and is explained in detail in this book. In RL, 'Curse of Dimensionality' is a major issue and author has used fuzzy inference system to handle this problem resulting in Fuzzy Q learning. Reinforcement learning works on exploitation and exploration policy and hence RL based controller may face stability issue. The main emphasis of this book is to introduce stability in RL based controller using Lyapunov theory. The proposed RL based controllers are simulated on various nonlinear systems including Inverted Pendulum and Robotic Manipulator. 56 pp. Englisch.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2021
ISBN 10: 6204732013 ISBN 13: 9786204732015
Librería: moluna, Greven, Alemania
EUR 37,23
Cantidad disponible: Más de 20 disponibles
Añadir al carritoKartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: KUMAR ABHISHEKAbhishek Kumar completed his Phd in Instrumentation & Control Engg. from University of Delhi (India), M.E. in Power Engg. from Jadavpur University (India) and B.Tech in Electronics & Comm. Engg. from UPTU (India). He ha.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing Dez 2021, 2021
ISBN 10: 6204732013 ISBN 13: 9786204732015
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 43,90
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book aims at providing basic introduction about reinforcement learning (RL), application of RL as controller and introducing stability in RL. Q-learning is most widely used RL technique and is explained in detail in this book. In RL, 'Curse of Dimensionality' is a major issue and author has used fuzzy inference system to handle this problem resulting in Fuzzy Q learning. Reinforcement learning works on exploitation and exploration policy and hence RL based controller may face stability issue. The main emphasis of this book is to introduce stability in RL based controller using Lyapunov theory. The proposed RL based controllers are simulated on various nonlinear systems including Inverted Pendulum and Robotic Manipulator.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 56 pp. Englisch.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2021
ISBN 10: 6204732013 ISBN 13: 9786204732015
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 44,59
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book aims at providing basic introduction about reinforcement learning (RL), application of RL as controller and introducing stability in RL. Q-learning is most widely used RL technique and is explained in detail in this book. In RL, 'Curse of Dimensionality' is a major issue and author has used fuzzy inference system to handle this problem resulting in Fuzzy Q learning. Reinforcement learning works on exploitation and exploration policy and hence RL based controller may face stability issue. The main emphasis of this book is to introduce stability in RL based controller using Lyapunov theory. The proposed RL based controllers are simulated on various nonlinear systems including Inverted Pendulum and Robotic Manipulator.