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

Venue: In. Proc. American Control Conference
DOI: 10.1109/ACC.2013.6580545
Link to Publication

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). 

@inproceedings{Agha-mohammadi-gscwca-2013, 
 author = {A. {Agha-mohammadi} and S. {Chakravorty} and N. M. {Amato}}, 
 booktitle = {2013 American Control Conference}, 
 doi = {10.1109/ACC.2013.6580545}, 
 number = {}, 
 pages = {4581-4586}, 
 title = {Graph-based stochastic control with constraints: A unified approach with perfect and imperfect measurements}, 
 volume = {}, 
 year = {2013} 
}