Random-World Semantics and Syntactic Independence for Expressive Languages

We consider three desiderata for a language combining logic and probability: logical expressivity, random-world semantics, and the existence of a useful syntactic condition for probabilistic independence. Achieving these three desiderata simultaneously is nontrivial. Expressivity can be achieved by...

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Main Authors: McAllester, David, Milch, Brian, Goodman, Noah D.
Other Authors: Leslie Kaelbling
Published: 2008
Online Access:http://hdl.handle.net/1721.1/41516
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author McAllester, David
Milch, Brian
Goodman, Noah D.
author2 Leslie Kaelbling
author_facet Leslie Kaelbling
McAllester, David
Milch, Brian
Goodman, Noah D.
author_sort McAllester, David
collection MIT
description We consider three desiderata for a language combining logic and probability: logical expressivity, random-world semantics, and the existence of a useful syntactic condition for probabilistic independence. Achieving these three desiderata simultaneously is nontrivial. Expressivity can be achieved by using a formalism similar to a programming language, but standard approaches to combining programming languages with probabilities sacrifice random-world semantics. Naive approaches to restoring random-world semantics undermine syntactic independence criteria. Our main result is a syntactic independence criterion that holds for a broad class of highly expressive logics under random-world semantics. We explore various examples including Bayesian networks, probabilistic context-free grammars, and an example from Mendelian genetics. Our independence criterion supports a case-factor inference technique that reproduces both variable elimination for BNs and the inside algorithm for PCFGs.
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spelling mit-1721.1/415162019-04-11T06:53:42Z Random-World Semantics and Syntactic Independence for Expressive Languages McAllester, David Milch, Brian Goodman, Noah D. Leslie Kaelbling Learning and Intelligent Systems We consider three desiderata for a language combining logic and probability: logical expressivity, random-world semantics, and the existence of a useful syntactic condition for probabilistic independence. Achieving these three desiderata simultaneously is nontrivial. Expressivity can be achieved by using a formalism similar to a programming language, but standard approaches to combining programming languages with probabilities sacrifice random-world semantics. Naive approaches to restoring random-world semantics undermine syntactic independence criteria. Our main result is a syntactic independence criterion that holds for a broad class of highly expressive logics under random-world semantics. We explore various examples including Bayesian networks, probabilistic context-free grammars, and an example from Mendelian genetics. Our independence criterion supports a case-factor inference technique that reproduces both variable elimination for BNs and the inside algorithm for PCFGs. 2008-05-05T15:45:52Z 2008-05-05T15:45:52Z 2008-05-03 MIT-CSAIL-TR-2008-025 http://hdl.handle.net/1721.1/41516 Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory 6 p. application/pdf application/postscript
spellingShingle McAllester, David
Milch, Brian
Goodman, Noah D.
Random-World Semantics and Syntactic Independence for Expressive Languages
title Random-World Semantics and Syntactic Independence for Expressive Languages
title_full Random-World Semantics and Syntactic Independence for Expressive Languages
title_fullStr Random-World Semantics and Syntactic Independence for Expressive Languages
title_full_unstemmed Random-World Semantics and Syntactic Independence for Expressive Languages
title_short Random-World Semantics and Syntactic Independence for Expressive Languages
title_sort random world semantics and syntactic independence for expressive languages
url http://hdl.handle.net/1721.1/41516
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