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Optimizing Probabilities in Probabilistic Logic Programs

Published online by Cambridge University Press:  23 September 2021

DAMIANO AZZOLINI Open the ORCID record for DAMIANO AZZOLINI [Opens in a new window]  and
FABRIZIO RIGUZZI Open the ORCID record for FABRIZIO RIGUZZI [Opens in a new window]
DAMIANO AZZOLINI
Affiliation:
Dipartimento di Ingegneria - University of Ferrara, Via Saragat 1, I-44122, Ferrara, Italy (e-mail: [email protected])
FABRIZIO RIGUZZI
Affiliation:
Dipartimento di Matematica e Informatica - University of Ferrara, Via Saragat 1, I-44122, Ferrara, Italy (e-mail: [email protected])
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Abstract

Probabilistic logic programming is an effective formalism for encoding problems characterized by uncertainty. Some of these problems may require the optimization of probability values subject to constraints among probability distributions of random variables. Here, we introduce a new class of probabilistic logic programs, namely probabilistic optimizable logic programs, and we provide an effective algorithm to find the best assignment to probabilities of random variables, such that a set of constraints is satisfied and an objective function is optimized.

Keywords

probabilistic logic programmingoptimizationconstraints
Type
Original Article
Information
Theory and Practice of Logic Programming , Volume 21 , Issue 5: 37th International Conference on Logic Programming Special Issue I , September 2021 , pp. 543 - 556
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Copyright
© The Author(s), 2021. Published by Cambridge University Press

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