Searching for "Recursive Markov chains" – sorted by Relevance.
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Recursive Markov chains, stochastic grammars, and monotone systems of non-linear equations
- Recursive Markov Chains, Stochastic Grammars, and Monotone Systems of Nonlinear Equations Kousha
- Cited by 25 (8 self) – Add To MetaCart
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PReMo: an analyzer for Probabilistic Recursive Models. Fuller report, with more experimental data
- Markov Chains, and their controlled/game extensions: (1-exit) Recursive Markov Decision Processes
- Cited by 1 (1 self) – Add To MetaCart
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Verifying Probabilistic Procedural Programs
- more naturally be modeled by recursive Markov chains ([EY04]), or equivalently, probabilistic pushdown
- Cited by 10 (2 self) – Add To MetaCart
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Recursive Markov decision processes and recursive stochastic games
- for their analysis and verification. These models extend Recursive Markov Chains (RMCs), introduced in [EY05a,EY05b
- Cited by 18 (5 self) – Add To MetaCart
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Algorithmic verification of recursive probabilistic state machines
- University Abstract. Recursive Markov Chains (RMCs) ([EY04]) are a natural abstract model of procedural
- Cited by 18 (5 self) – Add To MetaCart
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On the complexity of Nash equilibria and other fixed points (Extended Abstract)
- probabilities of stochastic context-free grammars, and of Recursive Markov Chains. We show that for some of them
- Cited by 7 (2 self) – Add To MetaCart
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On the convergence of Newton’s method for monotone systems of polynomial equations
- of stochastic context-free grammars, recursive Markov chains, and probabilistic pushdown automata. While
- Cited by 2 (1 self) – Add To MetaCart
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Recursive Concurrent Stochastic Games
- information) stochastic games that extend Recursive Markov Chains (RMCs) ([12,13]) with nonprobabilistic
- Cited by 7 (3 self) – Add To MetaCart
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Efficient qualitative analysis of classes of recursive markov decision processes and simple
- -probabilistic actions. They define infinitestate MDPs and SSGs that extend Recursive Markov Chains (RMCs) ([8, 9
- Cited by 4 (3 self) – Add To MetaCart
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Stochastic segment interaction models for biological sequence analysis
- dynamic programming recursions and Markov chain Monte Carlo (MCMC) simulation. Applications to modeling
- Cited by 1 (1 self) – Add To MetaCart

