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Mixed Nondeterministic-Probabilistic Automata: Blending graphical probabilistic models with nondeterminism

arXiv 2201.07474 ↗First posted 19 Jan 2022cs.AIcited by 0

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Abstract (arXiv)

Graphical models in probability and statistics are a core concept in the area of probabilistic reasoning and probabilistic programming-graphical models include Bayesian networks and factor graphs. In this paper we develop a new model of mixed (nondeterministic/probabilistic) automata that subsumes both nondeterministic automata and graphical probabilistic models. Mixed Automata are equipped with parallel composition, simulation relation, and support message passing algorithms inherited from graphical probabilistic models. Segala's Probabilistic Automatacan be mapped to Mixed Automata.

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References · 15

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  4. 2020Probabilistic Programs with Stochastic Conditioningcited by 9
  5. 2019Reactive Probabilistic Programmingcited by 6
  6. 2013Measure Transformer Semantics for Bayesian Machine Learningcited by 4
  7. 2019Semantics of higher-order probabilistic programs with conditioningcited by 4
  8. 2015Conditioning in Probabilistic Programmingcited by 3
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  10. 2017Concurrency and Probability: Removing Confusion, Compositionallycited by 2
  11. 2020Correctness by construction for probabilistic programscited by 2
  12. 2013Markov two-components processescited by 1
3 more
  1. 2014Stochastic Nondeterminism and Effectivity Functionscited by 1
  2. 2015Synchronization of Bernoulli sequences on shared letterscited by 1
  3. 2017Probabilistic Couplings for Probabilistic Reasoningcited by 1

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