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A MARKOV CHAIN CHOICE PROBLEM

Published online by Cambridge University Press:  10 December 2012

Sheldon M. Ross
Sheldon M. Ross*
Affiliation:
Epstein Department of Industrial and Systems Engineering, University of Southern California Los Angeles, CA 90089, USA E-mail: smross@usc.edu
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Abstract

Consider two independent Markov chains having states 0, 1, and identical transition probabilities. At each stage one of the chains is observed, and a reward equal to the observed state is earned. Assuming prior probabilities on the initial states of the chains it is shown that the myopic policy that always chooses to observe the chain most likely to be in state 1 stochastically maximizes the sequence of rewards earned in each period.

Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 27 , Issue 1 , January 2013 , pp. 53 - 55
Copyright
Copyright © Cambridge University Press 2013

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References

REFERENCES

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