There are 4 jobs that you can call in this module:
1- Play against an agent or make play 2 agents agaisnt each other (requires a .yaml configuration)
2- Preheat a model (Only works for The Show phase model).
3- Train agents models (requires a .yaml configuration)
4- Evaluate models in a given directory (requires a directory containing one or many configurations to evaluate, and the path where the models are located).
For you to play against our best agent:
python -m agent-cribbage Play --agent_yaml ./agent-cribbage/Configurations/Play_agent_vs_human.yaml
For you to play against the simple deterministic agent:
python -m agent-cribbage Play --agent_yaml ./agent-cribbage/Configurations/Play_deterministic_vs_human.yaml
To make play multiple agents against each other multiple games:
python -m agent-cribbage Play --agent_yaml ./agent-cribbage/Configurations/Play_agent_vs_random.yaml --number_games 1000
To preheat the model for phase 0 (The Show):
python -m agent-cribbage Preheat --model conv --epochs 3
To train a model giving a configuration:
python -m agent-cribbage Train --epochs 500 --number_games 200 --agent_yaml ./agent-cribbage/Configurations/Train_agent_ConvLstm_Dealer+split_discarded_MC.yaml --dataepochs2keep 5
To evaluate a directory containing multiple models:
python -m agent-cribbage Evaluate --number_games 5000 --config_dir ./agent-cribbage/Evaluate/Train_agent_ConvLstm_Dealer+split_discarded --model_dir ./Train_agent_ConvLstm_Dealer+split_discarded_MC