Measurable Cones and Stable, Measurable Functions

Resource type
Authors/contributors
Title
Measurable Cones and Stable, Measurable Functions
Abstract
We define a notion of stable and measurable map between cones endowed with measurability tests and show that it forms a cpo-enriched cartesian closed category. This category gives a denotational model of an extension of PCF supporting the main primitives of probabilistic functional programming, like continuous and discrete probabilistic distributions, sampling, conditioning and full recursion. We prove the soundness and adequacy of this model with respect to a call-by-name operational semantics and give some examples of its denotations.
Publication
Proceedings of the ACM on Programming Languages
Volume
2
Issue
POPL
Pages
1-28
Date
2017-12-27
Journal Abbr
Proc. ACM Program. Lang.
DOI
10/ggdjf8
ISSN
24751421
Accessed
2019-11-26T17:06:12Z
Library Catalog
Extra
ZSCC: 0000021 arXiv: 1711.09640
Citation
Ehrhard, T., Pagani, M., & Tasson, C. (2017). Measurable Cones and Stable, Measurable Functions. Proceedings of the ACM on Programming Languages, 2(POPL), 1–28. https://doi.org/10/ggdjf8
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