Optimal Control as a Graphical Model Inference Problem

Book One

Volume

Proceedings of the International Conference on Automated Planning and Scheduling, 23

Journal Presentation Track

In this paper we show the identification between stochastic optimal control computation and probabilistic inference on a graphical model for certain class of control problems. We refer to these problems as Kullback-Leibler (KL) control problems. We illustrate how KL control can be used to model a multi-agent cooperative game for which optimal control can be approximated using belief propagation when exact inference is unfeasible.

10.1609/icaps.v23i1.13573