A proof of imitation of Wasserstein inverse reinforcement learning for multi-objective optimization

05/17/2023

∙

by   Akira Kitaoka, et al.

∙

0

∙

share

We prove Wasserstein inverse reinforcement learning enables the learner's reward values to imitate the expert's reward values in a finite iteration for multi-objective optimizations. Moreover, we prove Wasserstein inverse reinforcement learning enables the learner's optimal solutions to imitate the expert's optimal solutions for multi-objective optimizations with lexicographic order.