mbpo_pytorch This is a re-implementation of the model-based RL algorithm MBPO in pytorch as described in the following paper: When to Trust Your Model: Model-Based Policy Optimization. This code is based on a previous paper in the NeurIPS reproducibility challenge that reproduces the result with a tensorflow ensemble model but shows a significant drop in performance with a pytorch ensemble model. This code re-implements the ensemble dynamics model with pytorch and closes the gap. Reproduced results The comparison are done […]

machin Machin is a reinforcement library designed for pytorch. Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA … Features 1. Automatic Starting from version 0.4.0, Machin now supports automatic config generation, you can get a configurationthrough: python -m machin.auto generate –algo DQN –env openai_gym –output config.json And automatically launch the experiment with pytorch lightning: python -m machin.auto launch –config config.json 2. Readable Compared to other reinforcement learning libraries such as the famous […]