Companion code for S. M. Katz, A. LeBihan, and M. J. Kochenderfer, “Learning an urban air mobility encounter model from expert preferences,” in Digital Avionics Systems Conference (DASC), 2019
reward_iteration.jl - Main file for algorithm implementation. Simply include this file and then run reward_iteration(num_iter).
ri_functions.jl - Contains all functions called by the reward iteration algorithm.
ri_const.jl - Defines constants used in reward iteration algorithm.
ri_types.jl - Defines types used in reward iteration algorithm.
landing_mdp.jl - Defines landing Markov Decision Process (MDP) using POMDPs.jl.
ri_test.jl - Contains functions and scripts to test algorithm performance automatically.
interactive_reward_iteration.jl - Main file for algorithm implementation. Include this file in Jupyter notebook rather than reward_iteration.jl.
InteractivePreferences.ipynb - Example Jupyter notebook for running the interactive version.
support_code.jl - Code used for plotting. From https://github.com/sisl/algforopt-notebooks.