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| Deciding probabilistic automata weak bisimulation: theory and practice | |
| Fioriti, LMF; Hashemi, V; Hermanns, H; Turrini, A | |
| 2016 | |
| Source | FORMAL ASPECTS OF COMPUTING
 |
| ISSN | 0934-5043 |
| Volume | 28Issue:1Pages:109-143 |
| English Abstract | Weak probabilistic bisimulation on probabilistic automata can be decided by an algorithm that needs to check a polynomial number of linear programming problems encoding weak transitions. It is hence of polynomial complexity. This paper discusses the specific complexity class of the weak probabilistic bisimulation problem, and it considers several practical algorithms and linear programming problem transformations that enable an efficient solution. We then discuss two different implementations of a probabilistic automata weak probabilistic bisimulation minimizer, one of them employing SAT modulo linear arithmetic as the solver technology. Empirical results demonstrate the effectiveness of the minimization approach on standard benchmarks, also highlighting the benefits of compositional minimization.; Weak probabilistic bisimulation on probabilistic automata can be decided by an algorithm that needs to check a polynomial number of linear programming problems encoding weak transitions. It is hence of polynomial complexity. This paper discusses the specific complexity class of the weak probabilistic bisimulation problem, and it considers several practical algorithms and linear programming problem transformations that enable an efficient solution. We then discuss two different implementations of a probabilistic automata weak probabilistic bisimulation minimizer, one of them employing SAT modulo linear arithmetic as the solver technology. Empirical results demonstrate the effectiveness of the minimization approach on standard benchmarks, also highlighting the benefits of compositional minimization. |
| Indexed Type | SCI |
| Keyword | Complexity Compositional Analysis Concurrency Efficiency Linear Programming Probabilistic Automata Satisfiability Modulo Theories Weak Bisimulation |
| Department | Univ Saarland, Dept Comp Sci, D-66123 Saarbrucken, Germany. Max Planck Inst Informat, D-66123 Saarbrucken, Germany. Chinese Acad Sci, Inst Software, State Key Lab Comp Sci, Beijing, Peoples R China. |
| Language | 英语 |
| WOS ID | WOS:000372262000006 |
| Citation statistics | |
| Content Type | 期刊论文 |
| URI | http://ir.iscas.ac.cn/handle/311060/17348 |
| Collection | 中国科学院软件研究所 |
| Recommended Citation GB/T 7714 | Fioriti, LMF,Hashemi, V,Hermanns, H,et al. Deciding probabilistic automata weak bisimulation: theory and practice[J]. FORMAL ASPECTS OF COMPUTING,2016,28(1):109-143. |
| APA | Fioriti, LMF,Hashemi, V,Hermanns, H,&Turrini, A.(2016).Deciding probabilistic automata weak bisimulation: theory and practice.FORMAL ASPECTS OF COMPUTING,28(1),109-143. |
| MLA | Fioriti, LMF,et al."Deciding probabilistic automata weak bisimulation: theory and practice".FORMAL ASPECTS OF COMPUTING 28.1(2016):109-143. |
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| art%3A10.1007%2Fs001（2164KB） | 开放获取 | License | Application Full Text | |||
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