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1 - Semantics of Probabilistic Programming: A Gentle Introduction

Published online by Cambridge University Press:  18 November 2020

By
Fredrik Dahlqvist ,
Alexandra Silva  and
Dexter Kozen
Edited by
Gilles Barthe ,
Joost-Pieter Katoen  and
Alexandra Silva
Gilles Barthe
Affiliation:
Max Planck Institute for Security and Privacy
Joost-Pieter Katoen
Affiliation:
RWTH Aachen University, Germany
Alexandra Silva
Affiliation:
University College London
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Summary

Reasoning about probabilistic programs is hard because it compounds the difficulty of classic program analysis with sometimes subtle questions of probability theory. Having precise mathematical models, or semantics, describing their behaviour is therefore particularly important. In this chapter, we review two probabilistic semantics. First, an operational semantics which models the local, step-by-step, behaviour of programs, then a denotational semantics describing global behaviour as an operator transforming probability distributions over memory states.

Keywords

Probabilistic programmingprogramming language semanticsimperative programming languagesmeasure theoryBanach spacesBanach lattices
Type
Chapter
Information
Foundations of Probabilistic Programming , pp. 1 - 42
Publisher: Cambridge University Press
Print publication year: 2020
Creative Commons
Creative Common License - CCCreative Common License - BY
This content is Open Access and distributed under the terms of the Creative Commons Attribution licence CC-BY 4.0 https://creativecommons.org/cclicenses/

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