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Probabilistic Program Abstractions

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arxiv 1705.09970 v2 pith:LBAJ27CY submitted 2017-05-28 cs.AI

classification cs.AI
keywords programabstractionsprobabilisticabstractionnon-deterministicprogramsabstractanalyze
verification ladder T0 review T1 audit T2 compute T3 formal
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Abstraction is a fundamental tool for reasoning about complex systems. Program abstraction has been utilized to great effect for analyzing deterministic programs. At the heart of program abstraction is the relationship between a concrete program, which is difficult to analyze, and an abstract program, which is more tractable. Program abstractions, however, are typically not probabilistic. We generalize non-deterministic program abstractions to probabilistic program abstractions by explicitly quantifying the non-deterministic choices. Our framework upgrades key definitions and properties of abstractions to the probabilistic context. We also discuss preliminary ideas for performing inference on probabilistic abstractions and general probabilistic programs.

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Cited by 1 Pith paper

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  1. Towards Unified Probabilistic Verification and Validation of Vision-Based Autonomy

    eess.SY 2025-08 reject novelty 5.0 of 10

    A pipeline that turns collected runs of a vision-based controller into an interval MDP, verifies a safety lower bound, and reuses Bayesian conformance to extend the bound to new environments.

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