Journal article

Trading performance for stability in Markov decision processes

Abstract:

We study controller synthesis problems for finite-state Markov decision processes, where the objective is to optimize the expected mean-payoff performance and stability (also known as variability in the literature). We argue that the basic notion of expressing the stability using the statistical variance of the mean payoff is sometimes insufficient, and propose an alternative definition.

We show that a strategy ensuring both the expected mean payoff and the variance below give...

Publication status:
Published
Peer review status:
Peer reviewed
Version:
Publisher's version

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Publisher copy:
10.1016/j.oceaneng.2016.08.007

Authors

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Department:
Oxford, MPLS, Computer Science
Role:
Author
Publisher:
Elsevier Publisher's website
Journal:
Journal of Computer and System Sciences Journal website
Volume:
125
Pages:
70–81
Publication date:
2016-10-05
Acceptance date:
2016-09-23
DOI:
EISSN:
1090-2724
ISSN:
0022-0000
Pubs id:
pubs:652697
URN:
uri:98165cbf-b07b-4de3-977c-46b3131b216b
UUID:
uuid:98165cbf-b07b-4de3-977c-46b3131b216b
Local pid:
pubs:652697