Model-Based Reinforcement Learning From Data to Continuous Actions with a Python-Based Toolbox
149,99 €
inkl. gesetzl. MwSt.,
Beschreibung
Produktdetails
Einband
Gebundene Ausgabe
Erscheinungsdatum
05.12.2022
Herausgeber
Maria Domenica Di BenedettoVerlag
John Wiley & Sons IncSeitenzahl
272
Maße (L/B/H)
23,5/15,7/1,9 cm
Gewicht
540 g
Auflage
1. Auflage
Sprache
Englisch
ISBN
978-1-119-80857-2
Explore a comprehensive and practical approach to reinforcement learning
Reinforcement learning is an essential paradigm of machine learning, wherein an intelligent agent performs actions that ensure optimal behavior from devices. While this paradigm of machine learning has gained tremendous success and popularity in recent years, previous scholarship has focused either on theory--optimal control and dynamic programming - or on algorithms--most of which are simulation-based.
Model-Based Reinforcement Learning provides a model-based framework to bridge these two aspects, thereby creating a holistic treatment of the topic of model-based online learning control. In doing so, the authors seek to develop a model-based framework for data-driven control that bridges the topics of systems identification from data, model-based reinforcement learning, and optimal control, as well as the applications of each. This new technique for assessing classical results will allow for a more efficient reinforcement learning system. At its heart, this book is focused on providing an end-to-end framework--from design to application--of a more tractable model-based reinforcement learning technique.
Model-Based Reinforcement Learning readers will also find:
* A useful textbook to use in graduate courses on data-driven and learning-based control that emphasizes modeling and control of dynamical systems from data
* Detailed comparisons of the impact of different techniques, such as basic linear quadratic controller, learning-based model predictive control, model-free reinforcement learning, and structured online learning
* Applications and case studies on ground vehicles with nonholonomic dynamics and another on quadrator helicopters
* An online, Python-based toolbox that accompanies the contents covered in the book, as well as the necessary code and data
Model-Based Reinforcement Learning is a useful reference for senior undergraduate students, graduate students, research assistants, professors, process control engineers, and roboticists.
Noch keine Bewertungen vorhanden
Verfassen Sie die erste Bewertung zu diesem Artikel
Helfen Sie anderen Kundinnen und Kunden durch Ihre Meinung.
Kurze Frage zu unserer Seite
Vielen Dank für dein Feedback
Wir nutzen dein Feedback, um unsere Produktseiten zu verbessern. Bitte habe Verständnis, dass wir dir keine Rückmeldung geben können. Falls du Kontakt mit uns aufnehmen möchtest, kannst du dich aber gerne an unseren Kund*innenservice wenden.
zum Kundenservice