Aggregation and optimal control of nearly completely decomposable Markov chains

R.W. Aldhaheri; H.K. Khalil; IEEE

doi:10.1109/CDC.1989.70343

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Conference proceeding

Aggregation and optimal control of nearly completely decomposable Markov chains

R.W. Aldhaheri, H.K. Khalil and IEEE

Proceedings of the 28th IEEE Conference on Decision and Control, pp.1277-1282 vol.2

1989

DOI: https://doi.org/10.1109/CDC.1989.70343

Abstract

Clustering algorithms

Cost function

Distributed computing

Infinite horizon

Iterative methods

Matrix decomposition

Minimization methods

Optimal control

Probability distribution

Steady-state

A study is made of the aggregation of nearly completely decomposable Markov chains. Three results are obtained. First, a similarity transformation that transforms the system into a singularly perturbed form is given. Second, an aggregation method for computing the exact steady-state probability distribution, as well as its O( in /sup k/) approximations, is derived. Third, a policy improvement algorithm based on the above aggregation method is developed for computing the optimal control that minimizes the average cost per stage over infinite horizon.< >

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Title: Aggregation and optimal control of nearly completely decomposable Markov chains
Creators - without role: R.W. Aldhaheri - King Abdulaziz University
H.K. Khalil
IEEE
Publication Details: Proceedings of the 28th IEEE Conference on Decision and Control, pp.1277-1282 vol.2
Publisher: IEEE
Identifiers: 9936316008331
Academic Unit: King Abdulaziz University
Language: English
Resource Type: Conference proceeding