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

Handle URI:
http://hdl.handle.net/10754/598428
Title:
Graph-based stochastic control with constraints: A unified approach with perfect and imperfect measurements
Authors:
Agha-mohammadi, Ali-akbar; Chakravorty, Suman; Amato, Nancy M.
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).
Citation:
Agha-mohammadi A, Chakravorty S, Amato NM (2013) Graph-based stochastic control with constraints: A unified approach with perfect and imperfect measurements. 2013 American Control Conference. Available: http://dx.doi.org/10.1109/ACC.2013.6580545.
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
2013 American Control Conference
KAUST Grant Number:
KUS-C1-016-04
Issue Date:
Jun-2013
DOI:
10.1109/ACC.2013.6580545
Type:
Conference Paper
Sponsors:
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).
Appears in Collections:
Publications Acknowledging KAUST Support

Full metadata record

DC FieldValue Language
dc.contributor.authorAgha-mohammadi, Ali-akbaren
dc.contributor.authorChakravorty, Sumanen
dc.contributor.authorAmato, Nancy M.en
dc.date.accessioned2016-02-25T13:20:33Zen
dc.date.available2016-02-25T13:20:33Zen
dc.date.issued2013-06en
dc.identifier.citationAgha-mohammadi A, Chakravorty S, Amato NM (2013) Graph-based stochastic control with constraints: A unified approach with perfect and imperfect measurements. 2013 American Control Conference. Available: http://dx.doi.org/10.1109/ACC.2013.6580545.en
dc.identifier.doi10.1109/ACC.2013.6580545en
dc.identifier.urihttp://hdl.handle.net/10754/598428en
dc.description.abstractThis 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).en
dc.description.sponsorshipThe 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).en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.titleGraph-based stochastic control with constraints: A unified approach with perfect and imperfect measurementsen
dc.typeConference Paperen
dc.identifier.journal2013 American Control Conferenceen
dc.contributor.institutionDept. of Computer Science and Engineeringen
dc.contributor.institutionDept. of Aerospace Engineering, Texas A&M University, TX 77843, USAen
kaust.grant.numberKUS-C1-016-04en
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