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


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
StatePublished - Jun 2013
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): KUS-C1-016-04
Acknowledgements: The work of Agha-mohammadi and Chakravorty is supported in part by NSFaward RI-1217991 and AFOSR Grant FA9550-08-1-0038 and the work of Aghamohammadiand Amato is supported in part by NSF awards CNS-0551685, CCF-0833199, CCF-0830753, IIS-0917266, IIS-0916053, EFRI-1240483, RI-1217991, byNSF/DNDO award 2008-DN-077-ARI018-02, by NIH NCI R25 CA090301-11, byDOE awards DE-FC52-08NA28616, DE-AC02-06CH11357, B575363, B575366, byTHECB NHARP award 000512-0097-2009, by Samsung, Chevron, IBM, Intel, Oracle/Sun and by Award KUS-C1-016-04, made by King Abdullah University of Scienceand Technology (KAUST).
This publication acknowledges KAUST support, but has no KAUST affiliated authors.


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