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Twin Delayed DDPG (TD3) PyTorch solution for Roboschool and Box2d environment

License: MIT License

Python 100.00%
ddpg td3 deep-reinforcement-learning openai-gym bipedalwalker pytorch pytorch-implmention reinforcement-learning openai-gym-environments lunar-lander

td3-pytorch-bipedalwalker-v2's Introduction

TD3-BipedalWalker-v2-PyTorch

PyTorch implementation of Twin Delayed DDPG (TD3) tested on the following environments:

Usage

  • To test a preTrained network : run test.py

  • To train a new network : run train.py

Dependencies

Trained and tested on:

Python 3.6
PyTorch 0.4.1
NumPy 1.15.3
gym 0.10.8
Roboschool 1.0.46
Pillow 5.3.0

Results

BipedalWalker-v2 (800 episodes) LunarLanderContinuous-v2 (1500 episodes)
RoboschoolWalker2d-v1 (lr=0.002, 1400 episodes) HalfCheetah-v1 (lr=0.002, 1400 episodes)

*The results are not consistent for BipedalWalker-v2 env

References

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