Abstract
We introduce and study Recursive Markov Chains (RMCs), which extend ordinary finite state Markov chains with the ability to invoke other Markov chains in a potentially recursive manner. They offer a natural abstract model for probabilistic programs with procedures, and are a probabilistic version of Recursive State Machines. RMCs generalize Stochastic Context-Free Grammars (SCFG) and multi-type Branching Processes, and are intimately related to Probabilistic Pushdown Systems. We focus here on termination and reachability analysis for RMCs. We present both positive and negative results for the general class of RMCs, as well as for important subclasses including SCFGs.
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Etessami, K., Yannakakis, M. (2005). Recursive Markov Chains, Stochastic Grammars, and Monotone Systems of Nonlinear Equations. In: Diekert, V., Durand, B. (eds) STACS 2005. STACS 2005. Lecture Notes in Computer Science, vol 3404. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31856-9_28
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DOI: https://doi.org/10.1007/978-3-540-31856-9_28
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