PyTorch Deep RL Library Guide

The deep reinforcement learning library in PyTorch is a toolkit for implementing deep reinforcement learning algorithms. This library provides implementations of many commonly used deep reinforcement learning algorithms, including Deep Q-Networks (DQN), Double Q-Networks (Double DQN), Advantage Actor-Critic (A3C), Deterministic Policy Gradients (DDPG), etc. Using this library, it is convenient to build, train, and evaluate deep reinforcement learning models. Additionally, this library also offers many useful tools and functions to assist users in conducting research and experiments in deep reinforcement learning more easily.