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Q-Learning for Cartpole (CMSC389F)
Python 96.13%
Makefile 3.87%
qlearn-cartpole's Introduction
- Use Python 3
- Use Colaboratory if you don't want a local setup
- Use
pip install
to install packages
- Gym: OpenAI Gym, a collection of environments to test RL algorithms on (e.g Atari games)
- Matplotlib: Fundamental plotting library for Python
- Numpy: Fundamental scientific computing package for python
- Run one episode on with a random policy
- "Train a policy" by creating random policies until you get one that gives a good return for an episode
- Test how well the above algorithm creates good policies by plotting the number episodes is required to produce a good policy, for 1000 trials
- Q-Learning on Cartpole
- DQN on Cartpole
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