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Shangtong Zhang
2018-04-24 23:22:20 -06:00
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@@ -11,7 +11,7 @@ Implemented algorithms:
* (Continuous/Discrete) Synchronous Proximal Policy Optimization (PPO)
* Action Conditional Video Prediction
Asynchronous algorithms below are removed in this repo but can be found in [the previous release](https://github.com/ShangtongZhang/DeepRL/releases/tag/v0.1)
Asynchronous algorithms below are removed in this repo but can be found in [v0.1](https://github.com/ShangtongZhang/DeepRL/releases/tag/v0.1)
* Async Advantage Actor Critic (A3C)
* Async One-Step Q-Learning
* Async One-Step Sarsa
@@ -20,6 +20,8 @@ Asynchronous algorithms below are removed in this repo but can be found in [the
* Distributed Deep Deterministic Policy Gradient (Distributed DDPG, aka D3PG)
* Parallelized Proximal Policy Optimization (P3O, similar to DPPO)
Support for Pytorch v0.3.x can be found in [v0.2](https://github.com/ShangtongZhang/DeepRL/releases/tag/v0.2)
# Curves
> Curves for CartPole are trivial so I didn't place it here. And there isn't any fixed random seed. The curves are generated in the same manner as OpenAI baselines (one run and smoothed by recent 100 episodes)
## DQN
@@ -52,14 +54,11 @@ Asynchronous algorithms below are removed in this repo but can be found in [the
Prediction is sampled after 110K iterations, and I only implemented one-step training
# Dependency
> Tested in macOS 10.12 and CentO/S 6.8
* OpenAI gym
* PyTorch v0.3.0
* Python 2.7 / 3.6
* [Roboschool](https://github.com/openai/roboschool) (Optional)
* [DeepMind Control Suite](https://github.com/deepmind/dm_control) & [DMControl2Gym](dm_control2gym) (Optional)
* [TensorboardX](https://github.com/lanpa/tensorboard-pytorch) (Optional)
* MacOS 10.12, CentO/S 6.8 and Ubuntu 16.04
* PyTorch v0.4.0
* Python 3.6 (recommended), 3.5 and 2.7
* Core dependencies: `pip install -r requirements.txt`
* Optional: [Roboschool](https://github.com/openai/roboschool), [DeepMind Control Suite](https://github.com/deepmind/dm_control)+[DMControl2Gym](dm_control2gym)
# Usage