Apprenticeship learning/imitation learning is interesting since for a given task we can learn from demonstrations of human or animals without access to a reward/cost function. Sometimes apprenticeship learning/imitation learning could be converted to learning reward/cost functions.
One of my imitation learning projects was Path Planning on Aerial Image by Imitation Learning. The idea was first to extract image feature maps, and then learn a cost map, which is a linear combination of the feature maps, that minimizes the cost of demonstrated routes. I did fair amount of image processing and handcrafting features in this project. I also implemented gradient descent for learning the cost map.
⬆️ Aerial image of university of pennsylvania
⬆️ Learned cost map for walking
⬆️ Learned cost map for driving
⬆️ Example of a planned walk route
⬆️ Example of a planned drive route