By Topic

Adaptive control of Markov chains, I: Finite parameter set

Sign In

Full text access may be available.

To access full text, please use your member or institutional sign in.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Borkar, V. ; University of California, Berkeley, CA, USA ; Varaiya, P.

Consider a controlled Markov chain whose transition probabilities depend upon an unknown parameter α taking values in finite set A . To each α is associated a prespecified stationary control law \phi(\alpha ) . The adaptive control law selects at each time t the control action indicated by \phi(\alpha _{t}) where αtis the maximum likelihood estimate of α. It is shown that αtconverges to a parameter α*such that the "closed-loop" transition probabilities corresponding to α*and \phi(\alpha ^{\ast }) are the same as those corresponding to α0and \phi(\alpha ) where α0is the true parameter. The situation when α0does not belong to the model set A is briefly discussed.

Published in:

Automatic Control, IEEE Transactions on  (Volume:24 ,  Issue: 6 )