Application ofComputable Distributions to the Semantics of Probabilistic Programs

Daniel Huang; Greg Morrisett; Bas Spitters

doi:10.1017/9781108770750.004

Application ofComputable Distributions to the Semantics of Probabilistic Programs

Daniel Huang, Greg Morrisett, Bas Spitters

Publikation: Bidrag til bog/antologi/rapport/proceeding › Bidrag til bog/antologi › Forskning › peer review

5 Citationer (Scopus)

Abstract

In this chapter, we explore how (Type-2) computable distributions can be used to give both (algorithmic) sampling and distributional semantics to probabilistic programs with continuous distributions. To this end, we sketch an encoding of computable distributions in a fragment of Haskell and show how topological domains can be used to model the resulting PCF-like language. We also examine the implications that a (Type-2) computable semantics has for implementing conditioning. We hope to draw out the connection between an approach based on (Type-2) computability and ordinary programming throughout the chapter as well as highlight the relation with constructive mathematics (via realizability).

Originalsprog	Engelsk
Titel	Foundations of Probabilistic Programming
Antal sider	46
Forlag	Cambridge University Press
Publikationsdato	1 jan. 2020
Sider	75-120
ISBN (Trykt)	9781108488518
ISBN (Elektronisk)	9781108770750
DOI	https://doi.org/10.1017/9781108770750.004
Status	Udgivet - 1 jan. 2020

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Application ofComputable Distributions to the Semantics of Probabilistic Programs

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