Reinforcement Learning

Build Artificial Intelligence (AI) agents using Deep Reinforcement Learning and PyTorch: A2C, REINFORCE, DQN, etc.

Build Artificial Intelligence (AI) agents using Deep Reinforcement Learning and PyTorch: From basic DQN to Rainbow DQN

Learn to apply Reinforcement Learning and Artificial Intelligence algorithms using Python, Pytorch and OpenAI Gym.

Learn to Build Powerful Deep RL Agents using Ray RLlib and OpenAI Gym

This book presents recent research in decision making under uncertainty, in particular reinforcement learning and learning with expert advice. The core elements of decision theory, Markov decision processes and reinforcement learning have not been previously collected in a concise volume. Our aim with this book was to provide a solid theoretical foundation with elementary proofs of the most important theorems in the field, all collected in one place, and not typically found in
introductory textbooks. This book is addressed to graduate students that are interested in statistical decision making under uncertainty and the foundations of reinforcement learning.

Learn to build robots that can automatically learn to behave well in their environments without explicit instructions.

OpenAI research, DeepMind research, Google research, Microsoft research