Nname: “Reinforcement Learning Assembly” description: “A collection of implementations of Ape-X and R2D2, together with necessary infrastructure such as prioritized replay and environments like Atari.” features: – “Implementation of Ape-X algorithm” – “Implementation of R2D2 algorithm” – “Prioritized replay infrastructure” – “Atari environments support” – “High-performance reinforcement learning framework” – “Scalable and modular design” usage: – “Training reinforcement learning agents using Ape-X” – “Training reinforcement learning agents using R2D2” – “Experimenting with prioritized replay buffer” – “Benchmarking reinforcement learning algorithms on Atari games” – “Developing custom reinforcement learning environments”开源项目 – 强化学习算法集合
该项目包含了Ape-X和R2D2算法的实现，并提供了必要的支持基础设施，如优先回放机制和Atari游戏环境。它是一个高性能的强化学习框架，具有可扩展和模块化的设计，适用于训练强化学习代理、实验优先回放缓冲区、在Atari游戏上基准测试强化学习算法以及开发自定义强化学习环境。
