On Convex Data-Driven Inverse Optimal Control for Nonlinear, Non-stationary and Stochastic Systems

arXiv:2306.13928v2 Announce Type: replace-cross
Abstract: This paper is concerned with a finite-horizon inverse control problem, which has the goal of reconstructing, from observations, the possibly non-convex and non-stationary cost driving the actions of an agent. In this context, we present a result enabling cost reconstruction by solving an optimization problem that is convex even when the agent cost is not and when the underlying dynamics is nonlinear, non-stationary and stochastic. To obtain this result, we also study a finite-horizon forward …

abstract agent arxiv context control cost cs.it cs.lg cs.ro data data-driven driving enabling horizon math.ds math.it math.oc paper problem replace stochastic systems type