Catalog

Hands-on intelligent agents with OpenAI Gym : a step-by-step guide to develop AI agents using deep reinforcement learning

Description:	1 online resource (1 volume) : illustrations
Publisher:	Birmingham, UK : Packt Publishing, 2018.
ISBN:	9781788835138 (electronic bk.)
Electronic resource	Access for Gordon College via EBSCOhost
▸Walks through the hands-on process of building intelligent agents from the basics and all the way up ... to solving complex problems including playing Atari games and driving a car autonomously in the CARLA simulator. Discusses various learning environments and how to transform real-world problems into learning environments and solve using the agents. Read More

Deep reinforcement learning hands-on : apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more

Description:	1 online resource (1 volume) : illustrations
Publisher:	Birmingham, UK : Packt Publishing, 2018.
Electronic resource	Access for Gordon College via EBSCOhost
▸This book is a practical, developer-oriented introduction to deep reinforcement learning (RL). ... Explore the theoretical concepts of RL, before discovering how deep learning (DL) methods and tools are making it possible to solve more complex and challenging problems than ever before. Apply deep RL methods to training your agent to beat arcade ... Read More

Optimal adaptive control & differential games by reinforcement learning principles

Description:	1 online resource (xiv, 288 pages).
Publisher:	London : Institution of Electrical Engineers, ©2013.
Electronic resource	Access for Gordon College via EBSCOhost

Reinforcement learning and approximate dynamic programming for feedback control

Description:	xxvi, 613 pages : illustrations ; 24 cm.
Publisher:	Piscataway, NJ : IEEE Press ; 2013.
ISBN:	9781118104200 (hardback)
1 of 1 copy available at NOBLE (All Libraries). 1 of 1 copy available at Gordon College. Library Location Call number Status Gordon College Stack Level 5 Q 325.6 .R464 2013 Available
▸"Reinforcement learning (RL) and adaptive dynamic programming (ADP) has been one of the most ... critical research fields in science and engineering for modern complex systems. This book describes the latest RL and ADP techniques for decision and control in human engineered systems, covering both single player decision and control and multi-player games. Edited by the pioneers of RL and ADP research, the book brings together ideas and methods from many fields and provides an important and timely guidance on controlling a wide variety of systems, such as robots, industrial processes, and economic decision-making"-- Read More
▸"Reinforcement learning and adaptive control can be useful for controlling a wide variety of systems ... including robots, industrial processes, and economical decision making"-- Read More

Hands-on reinforcement learning for games : implementing self-learning agents in games using artificial intelligence techniques

Description:	1 online resource (1 volume) : illustrations
Publisher:	Birmingham, UK : Packt Publishing, 2020.
ISBN:	9781839216770
Electronic resource	Access for Gordon College via EBSCOhost
▸The AI revolution is here and it is embracing games. Game developers are being challenged to enlist ... cutting edge AI as part of their games. In this book, you will look at the journey of building capable AI using reinforcement learning algorithms and techniques. You will learn to solve complex tasks and build next-generation games using a ... Read More

Control systems and reinforcement learning

Description:	xv, 435 pages :  illustrations (black and white) ; 27 cm.
Publisher:	Cambridge ; Cambridge University Press, 2022.
ISBN:	9781316511961 (hardback)
1 of 1 copy available at NOBLE (All Libraries). 1 of 1 copy available at Gordon College. Library Location Call number Status Gordon College Stack Level 5 Q 325.6 .M49 2022 Available
▸"A high school student can create deep Q-learning code to control her robot, without any ... understanding of the meaning of "deep" or "Q", or why the code sometimes fails. This book is designed to explain the science behind reinforcement learning and optimal control in a way that is accessible to students with a background in calculus and matrix algebra. A unique focus is algorithm design to obtain the fastest possible speed of convergence for learning algorithms, along with insight into why reinforcement learning sometimes fails. Advanced stochastic process theory is avoided at the start by substituting random exploration with more intuitive deterministic probing for learning. Once these ideas are understood, it is not difficult to master techniques rooted in stochastic control. These topics are covered in the second part of the book, starting with Markov chain theory and ending with a fresh look at actor-critic methods for reinforcement learning"-- Read More

Reinforcement learning with TensorFlow : a beginner's guide to designing self-learning systems with TensorFlow and OpenAI Gym

Description:	1 online resource (1 volume) : illustrations
Publisher:	Birmingham, UK : Packt Publishing, 2018.
ISBN:	9781788830713 (electronic bk.)
Electronic resource	Access for Gordon College via EBSCOhost