Task progress is intuitive and readily available task information that can guide an agent closer to the desired goal. Furthermore, a progress estimator can generalize to new situations. From this intuition, we propose a simple yet effective imitation learning from observation method for a goal-directed task using a learned goal proximity function as a task progress estimator, for better generalization to unseen states and goals. We obtain this goal proximity function from expert demonstrations a…