The folder eval_plots contains the figures comparing the Goal Skill Network agent against the monolithic agent, as well as the figures for hyperparameter tuning for Tabular SARSA.
The folder eval_results contains tables of evaluation results of each agent.
The folder training_plots contains figures showing the learning curves of the agents during training.
The folder q_values contains the learned action-value functions.
The file box_and_whiskers.py creates the box and whiskers plots.
The file eval_monolithic.py evaluates the monolithic agent.
The file taxi_agent_GSN.py defines the Goal Skill Network agent.
The file taxi_agent_monolithic.py defines the monolithic agent.
The file taxi_env.py modifies the Toy Taxi environment for the GSN agent.
The file taxi_planner_GSN.py defines the GTPyhop planner for the taxi environment, and runs the taxi environment
The file taxi_train_GSN.py trains the Goal Skill Network agent.
The file taxi_train_monolithic.py trains the monolithic taxi agent.