The book covers the major advancements and successes achieved in deep reinforcement learning by synergizing deep neural network architectures with reinforcement learning. The book also introduces readers to the concept of Reinforcement Learning, its advantages and why it's gaining so much popularity. Furthermore, it show readers how to put the concepts to practical use with the help of TensorFlow and OpenAI Gym to train efficient deep reinforcement learning neural networks. The book also discusses reinforcement learning and the rewarding system: Markov Decision Processes (MDPs), Monte Carlo tree searches, dynamic programming such as policy and value iteration, temporal difference learnings such as Q-learning and SARSA.


论坛上有其他格式的。这是高清PDF版本。