Multi-Objective Constraint Inference using Inverse reinforcement learning

ArXi:2605.06951v1 Announce Type: new Constraint inference is widely considered essential to align reinforcement learning agents with safety boundaries and operational guidelines by observing expert nstrations. However, existing approaches typically assume homogeneous nstrations (i.e., generated by a single expert or multiple experts with identical objectives). They also have limited ability to capture individual preferences and often suffer from computational inefficiencies. In this paper, we