RL Base强化学习：信赖域策略优化（TRPO）算法Pytorch 实现

# PyTorch implementation of TRPO Try my implementation of [PPO](github.com/ikostrikov/pytorch-a2c-ppo-acktr/) (aka newer better variant of TRPO), unless you need to you TRPO for some specific reasons. ## This is a PyTorch implementation of ["Trust Region Policy Optimization (TRPO)"](https://arxiv.org/abs/1502.05477). This is code mostly ported from [original implementation by John Schulman](https://github.com/joschu/modular_rl). In contrast to [another implementation of TRPO in PyTorch](https://github.com/mjacar/pytorch-trpo), this implementation uses exact Hessian-vector product instead of finite differences approximation. ## Contributions Contributions are very welcome. If you know how to make this code better, don't hesitate to send a pull request. ## Usage ``` python main.py --env-name "Reacher-v1" ``` ## Recommended hyper parameters InvertedPendulum-v1: 5000 Reacher-v1, InvertedDoublePendulum-v1: 15000 HalfCheetah-v1, Hopper-v1, Swimmer-v1, Walker2d-v1: 25000 Ant-v1, Humanoid-v1: 50000 ## Results More or less similar to the original code. Coming soon. ## Todo - [ ] Plots. - [ ] Collect data in multiple threads.