Recent advances in Reinforcement Learning, grounded on combining classical theoretical
results with Deep Learning paradigm, led to breakthroughs in many artificial intelligence …

This textbook covers principles behind main modern deep reinforcement learning algorithms
that achieved breakthrough results in many domains from game AI to robotics. All required …

Abstract Deep Reinforcement Learning is a topic that has gained a lot of attention recently,
due to the unprecedented achievements and remarkable performance of such algorithms in …

From Reinforcement Learning to Deep Reinforcement Learning: An Overview | SpringerLink
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Deep reinforcement learning is the combination of reinforcement learning (RL) and deep
learning. This field of research has been able to solve a wide range of complex …

This chapter aims to briefly introduce the fundamentals for deep learning, which is the key
component of deep reinforcement learning. We will start with a naive single-layer network …

Deep reinforcement learning (DRL) combines deep learning (DL) with a reinforcement
learning (RL) architecture. It has been able to perform a wide range of complex decision …

Reinforcement Learning has evolved a long way with the enhancements from deep
learning. Recent research efforts into combining deep learning with Reinforcement Learning …

This book is about reinforcement learning and takes you from the basics through advanced
topics. Though this book assumes no prior knowledge of the field of reinforcement learning …

Deep reinforcement learning (deep RL) combines deep learning and reinforcement
learning, in which artificial agents learn to solve sequential decision-making problems. In the …