Title :
A methodology for the adaptive control of Markov chains under partial state information
Author :
Fernández-Gaucherand, Emmanuel ; Arapostathis, Aristotle ; Marcus, Steven I.
Author_Institution :
Dept. of Syst. & Ind. Eng., Arizona Univ., Tucson, AZ, USA
Abstract :
A stochastic adaptive control problem where complete state information is not available to the controller is considered. The system is modeled as a finite stochastic automaton. These models are a slight generalization of the more common partially observable controlled Markov chain models
Keywords :
Markov processes; State estimation; adaptive control; finite automata; state estimation; stochastic automata; stochastic systems; Markov chains; finite stochastic automaton; partial state information; stochastic adaptive control; Adaptive control; Automata; Automatic control; Cost function; Optimal control; Process control; State-space methods; Stochastic processes; Stochastic systems; Tin;
Conference_Titel :
Decision and Control, 1992., Proceedings of the 31st IEEE Conference on
Conference_Location :
Tucson, AZ
Print_ISBN :
0-7803-0872-7
DOI :
10.1109/CDC.1992.371318
