TD3-BipedalWalker-v2-PyTorch

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

• Bipedal Walker v2

• Lunar Lander Continuous v2

• Walker2d v1 (Roboschool)

• HalfCheetah v1 (Roboschool)

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

• Official TD3 paper and code

• OpenAI SpinningUp in Deep RL