Code for "Reward Design For An Online Reinforcement Learning Algorithm For Supporting Oral Self-Care”
The package is organized in the following way:
- Fitting parameters for the simualtion environment base model: fitting_simulation_base_model.py
- Forming the prior for the RL algorithm: forming_prior_using_robas_2.py
- Simulation Envrionment Code: simulation_environment.py
- RL Algorithm Code: rl_algorithm.py
- Main Experiment Function: rl_experiments.py
- Code for parallelization and calling experiment function: run_rl_experiment.py
- Computing metrics and plotting figures: metric_computations.py and plot_figures.py