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LTL model checking of interval Markov chains

Abstract:

Interval Markov chains (IMCs) generalize ordinary Markov chains by having interval-valued transition probabilities. They are useful for modeling systems in which some transition probabilities depend on an unknown environment, are only approximately known, or are parameters that can be controlled. We consider the problem of computing values for the unknown probabilities in an IMC that maximize the probability of satisfying an ω-regular specification. We give new upper and lower bounds on the c...

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Publisher copy:
10.1007/978-3-642-36742-7_3

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
Journal:
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) More from this journal
Volume:
7795 LNCS
Pages:
32-46
Publication date:
2013-01-01
DOI:
EISSN:
1611-3349
ISSN:
0302-9743
Language:
English
Pubs id:
pubs:389457
UUID:
uuid:a7cc4ff6-91b2-49a5-bba3-feacda6a3909
Local pid:
pubs:389457
Source identifiers:
389457
Deposit date:
2013-11-17

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