Solved Bipedal Walker Environment about td3-pytorch-bipedalwalker-v2

[nikhilbarhate99]

I think I got confused between number of episodes and number of updates. Still not sure though, considering different algorithms use different number of episodes per update.
No, I have not tested it with large averaging window. But I think that's because all value based methods tend to be unstable. TD3 should have reduced this instability but it also depends on the environment and the reward signal, which could be the problem in this env.
Also, the variance can be reduced by decaying the noise in later stages (not implemented in this repo) and deleting the older experiences which should solve the forgetting problem, but I would suggest you to test your algorithm on different environment (I did not face this problem on the lunar lander env).