Active inference for Robot control: A Factor Graph Approach - Vanderbroeck, Mees; Baioumy, Mohamed; van der Lans, Daan; de Rooij, Rens; van der Werf, Tiis (Student Undergraduate Research E-journal!, 2019)
Active Inference provides a framework for perception, action and learning, where the optimization is done by minimizing the Free-Energy of a system. This paper explores whether active inference can be used for closedloop control of a 1 degree of freedom robot arm. This is done by implementing variational message passing on Forney-style factor graphs; a probabilistic programming framework. We show that an active inference controller with variational message passing can perform state estimation and control at the same time.