Graph-based stochastic control with constraints: A unified approach with perfect and imperfect measurements

Ali-akbar Agha-mohammadi, Suman Chakravorty, Nancy M. Amato

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper is concerned with the problem of stochastic optimal control (possibly with imperfect measurements) in the presence of constraints. We propose a computationally tractable framework to address this problem. The method lends itself to sampling-based methods where we construct a graph in the state space of the problem, on which a Dynamic Programming (DP) is solved and a closed-loop feedback policy is computed. The constraints are seamlessly incorporated to the control policy selection by including their effect on the transition probabilities of the graph edges. We present a unified framework that is applicable both in the state space (with perfect measurements) and in the information space (with imperfect measurements).
Original languageEnglish (US)
Title of host publication2013 American Control Conference
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISBN (Print)9781479901784
DOIs
StatePublished - Jun 2013
Externally publishedYes

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