Twin Delayed DDGP

Pytorch Implementation of Twin Delayed Deep Deterministic Policy Gradients Algorithm for Continuous Control as described by the paper Addressing Function Approximation Error in Actor-Critic Methods by Scott Fujimoto, Herke van Hoof, David Meger.

Results

BipedalWalker-V3

Environment Link: https://gym.openai.com/envs/BipedalWalker-v2/

Mean Reward: 295.263390447903 sampled over 20 evaluation episodes.

Experiment Conducted on Free-P5000 instance provided by Paperspace Gradient.

LunarLanderContinuous-V2

Environment Link: https://gym.openai.com/envs/LunarLanderContinuous-v2/

Mean Reward: 272.55341062406666 sampled over 20 evaluation episodes.

Experiment Conducted on Free-P5000 instance provided by Paperspace Gradient.

Reference

@misc{1802.09477,
    Author = {Scott Fujimoto and Herke van Hoof and David Meger},
    Title = {Addressing Function Approximation Error in Actor-Critic Methods},
    Year = {2018},
    Eprint = {arXiv:1802.09477},
}