An example-rich guide for beginners to start their reinforcement and deep reinforcement learning journey with state-of-the-art distinct algorithms

Key Features

Covers a vast spectrum of basic-to-advanced RL algorithms with mathematical explanations of each algorithm
Learn how to implement algorithms with code by following examples with line-by-line explanations
Explore the latest RL methodologies such as DDPG, PPO, and the use of expert demonstrations

Book Description

With significant enhancements in the quality and quantity of algorithms in recent...

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