Active inference for Robot control: A Factor Graph Approach

  • Mees Vanderbroeck Delft University of Technology
  • Mohamed Baioumy Delft University of Technology
  • Daan van der Lans Delft University of Technology
  • Rens de Rooij Delft University of Technology
  • Tiis van der Werf Delft University of Technology


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.

How to Cite
VANDERBROECK, Mees et al. Active inference for Robot control: A Factor Graph Approach. Student Undergraduate Research E-journal!, [S.l.], v. 5, p. 1-5, dec. 2019. ISSN 2468-0443. Available at: <>. Date accessed: 30 nov. 2020. doi: