Active inference for Robot control: A Factor Graph Approach

Authors

  • 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

DOI:

https://doi.org/10.25609/sure.v5.4181

Keywords:

Factor graphs, free-energy principle, active inference, closed-loop control, variational message passing

Abstract

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.

Additional Files

Published

2019-12-03

How to Cite

Vanderbroeck, M., Baioumy, M., van der Lans, D., de Rooij, R., & van der Werf, T. (2019). Active inference for Robot control: A Factor Graph Approach. Student Undergraduate Research E-Journal!, 5, 1–5. https://doi.org/10.25609/sure.v5.4181

Issue

Vol. 5 (2019): Student Research Conference 2019

Section

General Category

License

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