This project is a Reinforcement Learning homework of course Applied Deep Learning. I built an Atari game bot with reinforcement learning, specifically policy gradient and deep-Q learning. Spec is given in the following slides and experiment result is in the report.
Type the following command to install OpenAI Gym Atari environment.
$ pip3 install opencv-python gym gym[atari]
Please refer to OpenAI's page if you have any problem while installing.
training policy gradient:
$ python3 main.py --train_pg --model_name pg --log_name pg.log
testing policy gradient:
$ python3 test.py --test_pg
training DQN:
$ python3 main.py --train_dqn --model_name dqn --log_name dqn.log --dqn_gamma 0.9
testing DQN:
$ python3 test.py --test_dqn
If you want to see your agent playing the game,
$ python3 test.py --test_[pg|dqn] --do_render
- p1_pg: python3 p1_pg.py
- p1_dqn: python3 p1_dqn.py
- p2: python3 p2.py
- p3 variance reduction: python3 p3_pg.py
- p3 DDQN: python3 p3_dqn.py