Publication | Open Access
Probabilistic predicate transformers
301
Citations
19
References
1996
Year
Bayesian Decision TheoryEngineeringProbabilistic LearningProbabilistic ComputationState SpaceFormal VerificationProbabilistic OntologyNon-monotonic LogicProbability LogicData ScienceProbabilistic ReasoningBayesian ModelingHealthiness ConditionsProbabilistic SystemImperative ProgramsComputer ScienceProbability TheoryProbabilistic Predicate TransformersBayesian StatisticsAutomated ReasoningProbabilistic VerificationFormal MethodsFirst-order LogicProbabilistic Programming
Probabilistic predicates generalize standard predicates over a state space; with probabilistic predicate transformers one thus reasons about imperative programs in terms of probabilistic pre- and postconditions. Probabilistic healthiness conditions generalize the standard ones, characterizing “real” probabilistic programs, and are based on a connection with an underlying relational model for probabilistic execution; in both contexts demonic nondeterminism coexists with probabilistic choice. With the healthiness conditions, the associated weakest-precondition calculus seems suitable for exploring the rigorous derivation of small probabilistic programs.
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