Model-Based Reinforcement Learning: From Data to C ontinuous Actions with a Python-based Toolbox / Nejlevnější knihy
Model-Based Reinforcement Learning: From Data to C ontinuous Actions with a Python-based Toolbox

Kód: 35357753

Model-Based Reinforcement Learning: From Data to C ontinuous Actions with a Python-based Toolbox

Autor Jun Liu, Milad Farsi

Explore a comprehensive and practical approach to reinforcement learningReinforcement learning is an essential paradigm of machine learning, wherein an intelligent agent performs actions that ensure optimal behavior from devices. ... celý popis

2972


Skladem u dodavatele
Odesíláme za 9-15 dnů
Přidat mezi přání

Mohlo by se vám také líbit

Darujte tuto knihu ještě dnes
  1. Objednejte knihu a zvolte Zaslat jako dárek.
  2. Obratem obdržíte darovací poukaz na knihu, který můžete ihned předat obdarovanému.
  3. Knihu zašleme na adresu obdarovaného, o nic se nestaráte.

Více informací

Více informací o knize Model-Based Reinforcement Learning: From Data to C ontinuous Actions with a Python-based Toolbox

Nákupem získáte 297 bodů

Anotace knihy

Explore a comprehensive and practical approach to reinforcement learningReinforcement 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 dataModel-Based Reinforcement Learning is a useful reference for senior undergraduate students, graduate students, research assistants, professors, process control engineers, and roboticists.

Parametry knihy

2972

Oblíbené z jiného soudku



Osobní odběr Praha, Brno a 47531 dalších

Copyright ©2008-26 nejlevnejsi-knihy.cz Všechna práva vyhrazenaSoukromíCookies


Můj účet: Přihlásit se
Všechny knihy světa na jednom místě. Navíc za skvělé ceny.

Nákupní košík ( prázdný )

Vyzvednutí v Balikovně a PPL
boxech
zdarma nad 1 499 Kč.

Nacházíte se: