# -NIPS-2017-Learning-to-Run

Reinforcement learning environments with musculoskeletal models   

https://www.crowdai.org/challenges/nips-2017-learning-to-run  

CANDIDATE ALGORITHMS:  

Depp Deterministic Policy Gradient---DDPG(https://arxiv.org/abs/1509.02971)  

Recurrent Deterministic Policy Gradient---RDPG(https://arxiv.org/pdf/1512.04455.pdf)  

Trust  

MOTIVATION:  

In this case, we are manipulating the muscles rather than the velocity of the body parts, i.e., if I understood the problem correctly, we are changing the acceleration, which should be considered a second-order markov chain. LSTM and recurrent network might be able to capture the long short term dependencies.  

FOlDERS AND FILES:  

DDPG: The standard implementation of ddpg in tensorflow, following the pesudocode in the paper.  

RDPG: The recurrent version of the ddpg in tensorflow(There are complications that have not been resolved)

DEPENDENCIES:

Tensorflow

numpy

math