Mixed Nondeterministic-Probabilistic Automata: Blending graphical probabilistic models with nondeterminism
Albert Benveniste, Jean-Baptiste Raclet · arXiv (Cornell University) · 2022
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.