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Reinforcement learning environments with musculoskeletal models

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-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)
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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

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Reinforcement learning environments with musculoskeletal models


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