Eager Markov chains

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4218 LNCS, Issue , 2006, Pages 24-38

  Abdulla, Parosh Aziz ^a   Henda, Noomene Ben ^a   Mayr, Richard ^b   Sandberg, Sven ^a  

^a UPPSALA UNIVERSITY   (Sweden)

^b NORTH CAROLINA STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION THEORY; COMPUTATIONAL COMPLEXITY; FUNCTIONS; PROBLEM SOLVING; VECTORS;

BOUNDING FUNCTIONS; PROBABILISTIC LOSSY CHANNEL SYSTEMS; REACHABILITY ANALYSIS;

MARKOV PROCESSES;

EID: 33845186937     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11901914_5     Document Type: Conference Paper

References (31)

1. P. A. Abdulla, C. Baier, P. Iyer, and B. Jonsson. Reasoning about probabilistic lossy channel systems. In Proc. CONCUR 2000, 2000.
2. P. A. Abdulla, K. Ǒerāns, B. Jonsson, and T. Yih-Kuen. Algorithmic analysis of programs with well quasi-ordered domains. Information and Computation, 160:109-127, 2000.
3. P. A. Abdulla, N. B. Henda, and R. Mayr. Verifying infinite Markov chains with a finite attractoror the global coarseness property. In Proc. LICS '05, pp. 127-136, 2005.
4. P. A. Abdulla, N. B. Henda, R. Mayr, and S. Sandberg. Eager Markov chains. Technical Report 2006-009, Department of Information Technology, Uppsala University, 2006.
5. P. A. Abdulla, N. B. Henda, R. Mayr, and S. Sandberg. Limiting behavior of Markov chains with eager attractors. In Proc. QEST '06. IEEE Computer Society Press, 2006. To appear.
6. P. A. Abdulla and A. Rabinovich. Verification of probabilistic systems with faulty communication. In Proc. FOSSACS '03, vol. 2620 of LNCS, pp. 39-53, 2003.
7. E. Asarin and P. Collins. Noisy Turing machines. In Proc. ICALP '05, pp. 1031-1042, 2005.
8. A. Aziz, K. Sanwal, V. Singhal, and R. Brayton. Model-checking continuous-time Markov chains. ACM Trans. on Computational Logic, 1(1): 162-170, 2000.
9. C. Baier, N. Bertrand, and P. Schnoebelen. A note on the attractor-property of infinite-state Markov chains. Information Processing Letters, 97(2):58-63, 2006.
10. C. Baier and B. Engelen. Establishing qualitative properties for probabilistic lossy channel systems. In Katoen, editor, ARTS '99, Formal Methods for Real-Time and Probabilistic Systems, 5th Int. AMAST Workshop, vol. 1601 of LNCS, pp. 34-52. Springer Verlag, 1999.
11. C. Baier, B. Haverkort, H. Hermanns, and J.-P. Katoen. Model checking meets performance evaluation. ACM Performance Evaluation Review, 32(2): 10-15, 2005.
12. C. Baier, B. R. Haverkort, H. Hermanns, and J.-P. Katoen. Automated performance and dependability evaluation using model checking. In Proc. Performance 2002, pp. 261-289, 2002.
13. N. Bertrand and P. Schnoebelen. Model checking lossy channels systems is probably decidable. In Proc. FOSSACS03, vol. 2620 of LNCS, pp. 120-135, 2003.
14. T. Brázdil and A. Kučera. Computing the expected accumulated reward and gain for a subclass of infinite Markov chains. In Proc. FSTTCS '05, vol. 3821 of LNCS, pp. 372-383, 2005.
15. E. Clarke, O. Grumberg, and D. Peled. Model Checking. MIT Press, Dec. 1999.
16. C. Courcoubetis and M. Yannakakis. The complexity of probabilistic verification. Journal of the ACM, 42(4):857-907, 1995.
17. L. de Alfaro, M. Z. Kwiatkowska, G. Norman, D. Parker, and R. Segala. Symbolic model checking of probabilistic processes using mtbdds and the Kronecker representation. In Proc. TACAS '00, vol. 1785 of LNCS, pp. 123-137, 2000.
18. J. Esparza and K. Etessami. Verifying probabilistic procedural programs. In Proc. FSTTCS '04, pp. 16-31, 2004.
19. I. Esparza, A. Kueera, and R. Mayr. Model checking probabilistic pushdown automata. In Proc. LICS '04, pp. 12-21, 2004.
20. J. Esparza, A. Kučera, and R. Mayr. Quantitative analysis of probabilistic pushdown automata: Expectations and variances. In Proc. LICS '05, pp. 117-126, 2005.
21. K. Etessami and M. Yannakakis. Algorithmic verification of recursive probabilistic state machines. In Proc. TACAS '05, vol. 3440 of LNCS, pp. 253-270, 2005.
22. K. Etessami and M. Yannakakis. Recursive Markov chains, stochastic grammars, and monotone systems of non-linear equations. In Proc. STACS '05, vol. 2996 of LNCS, pp. 340-352, 2005.
23. K. Etessami and M. Yannakakis. Recursive Markov decision processes and recursive stochastic games. In Proc. ICALP '05, vol. 3580 of LNCS, pp. 891-903, 2005.
24. W. Feller. An Introduction to Probability Theory and Its Applications, vol. 1. Wiley & Sons, second edition, 1966.
25. S. Hart and M. Shark. Probabilistic temporal logics for finite and bounded models. In Proc. STOC '84, pp. 1-13, 1984.
26. P. Iyer and M. Narasimha. Probabilistic lossy channel systems. In TAPSOFT '97: Theory and Practice of Software Development, vol. 1214 of LNCS, pp. 667-681, 1997.
27. M. Kwiatkowska, G. Norman, and D. Parker. Probabilistic model checking in practice: Case studies with PRISM. ACM Performance Evaluation Review, 32(2):16-21, 2005.
28. D. Lehmann and S. Shelah. Reasoning with time and chance. Information and Control, 53:165-198, 1982.
29. A. Rabinovich. Quantitative analysis of probabilistic lossy channel systems. In Proc. ICALP '03, vol. 2719 of LNCS, pp. 1008-1021, 2003.
30. P. Stǎnicǎ. Good lower and upper bounds on binomial coefficients. Journal of Inequalities in Pure and Applied Mathematics, 2(3), 2001.
31. M. Vardi. Automatic verification of probabilistic concurrent finite-state programs. In Proc. FOCS '85, pp. 327-338, 1985.