Optimal Control as a Graphical Model Inference Problem
DOI:
https://doi.org/10.1609/icaps.v23i1.13573Keywords:
Optimal Control, Kullback-Leibler, Graphical Model, Approximate Inference, Belief PropagationAbstract
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.
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Published
2013-06-02
How to Cite
Kappen, H., Gomez, V., & Opper, M. (2013). Optimal Control as a Graphical Model Inference Problem. Proceedings of the International Conference on Automated Planning and Scheduling, 23(1), 472-473. https://doi.org/10.1609/icaps.v23i1.13573
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Journal Presentation Track