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A simple baseline for mountain-car @ gym

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greatwallet/mountain-car

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Simple Solvers forMountainCar-v0 andMountainCarContinuous-v0 @ gym. Methods including Q-learning, SARSA, Expected-SARSA, DDPG and DQN.

Demo

Testing Environment

  • gym
  • pytorch 1.3.1
  • torchvision 0.4.2

MountainCar-v0

Before run any script, please check out the parameters defined in the script and modify any of them as you please.

Train with Temporal-Difference Method

python TD.py

TODO:Train with DQN Method

Adapted fromREINFORCEMENT LEARNING (DQN) TUTORIAL in pytorch tutorials, which originally deals withCartPole Problem.

DQN method has not been run and tested.

python DQN.py

inference with Temporal-Difference Method

python inference.py

MountainCarContinuous-v0

Train with DDPG

Adapted fromDeep Reinforcement Learning Algorithms with PyTorch but rewritten in complete pytorch format, and redundant functions are removed.

python train_continuous.py

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