Run the game and:
python src/train.py -g 0 -o model/dqn --random 0.4 --random_reduction 0.00002 --min_random 0.1
Options:
- -g, --gpu: (optional) GPU device index (default: -1).
- -i, --input: (optional) input model file path without extension.
- -o, --output: (required) output model file path without extension.
- -r, --random: (optional) randomness of playing (default: 0.2).
- --pool_size: (optional) number of frames of memory pool (default: 50000).
- --random_reduction: (optional) randomness reduction rate per iteration (default: 0.00002).
- --min_random: (optional) minimum randomness of playing (default: 0.1).
- --double_dqn: (optional) use Double DQN algorithm
- --update_target_interval: (optional) interval to update target Q function of Double DQN (default: 2000)
MIT License