Title :
Competitive Markov decision processes with partial observation
Author :
Hsu, Shun-Pin ; Arapostathis, An
Author_Institution :
Dept. of Electr. Eng., Nat. Chi-Nan Univ., Nantou
Abstract :
We study a class of Markov decision processes (MDPs) in the infinite time horizon where the number of controllers is two and the observation information is allowed to be imperfect. Suppose the system, space and action space are both finite, and the controllers, having conflicting interests with each other, make decisions independently to seek their own best long-run average profit. Under the hypothesis that at least one system state is perfectly observable and accessible (by each system state no matter what actions are taken), we prove the existence of optimal policies for both controllers and characterize them by the min-max type of dynamic programming equations. An example on a class of machine maintenance process is presented to show our work
Keywords :
Markov processes; competitive algorithms; dynamic programming; optimal control; stochastic systems; competitive Markov decision processes; dynamic programming equations; infinite time horizon; optimal control; partial observation; stochastic system; Airplanes; Computer networks; Control systems; Cost function; Equations; Nash equilibrium; Optimal control; Processor scheduling; Stochastic processes; Stochastic systems;
Conference_Titel :
Systems, Man and Cybernetics, 2004 IEEE International Conference on
Conference_Location :
The Hague
Print_ISBN :
0-7803-8566-7
DOI :
10.1109/ICSMC.2004.1398303