Reinforcement Learning for Finance begins by describing methods for training neural networks. Next, it discusses CNN and RNN – two …
Reinforcement learning (RL) has led to several breakthroughs in AI. The use of the Q-learning (DQL) algorithm alone has helped …
The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active …
New edition of the bestselling guide to deep reinforcement learning and how it's used to solve complex real-world problems. Revised …
Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an …
We all learn through trial and error. We avoid the things that cause us to experience pain and failure. We …
Explore reinforcement learning (RL) techniques to build cutting-edge games using Python libraries such as PyTorch, OpenAI Gym, and TensorFlow Key …
This book surveys the state of the art in explainable and interpretable reinforcement learning (RL) as relevant for robotics. While …
Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance …
Develop self-learning algorithms and agents using TensorFlow and other Python tools, frameworks, and libraries Key Features • Learn, develop, and …
Adaptive controllers and optimal controllers are two distinct methods for the design of automatic control systems. Adaptive controllers learn online …
