Optimizing Probabilities in Probabilistic Logic Programs

被引：3
|
作者：
Azzolini, Damiano [1 ]
Riguzzi, Fabrizio [2 ]
机构：
[1] Univ Ferrara, Dipartimento Ingn, Via Saragat 1, I-44122 Ferrara, Italy
[2] Univ Ferrara, Dipartimento Matemat & Informat, Via Saragat 1, I-44122 Ferrara, Italy
来源：
THEORY AND PRACTICE OF LOGIC PROGRAMMING | 2021年 / 21卷 / 05期
关键词：
probabilistic logic programming; optimization; constraints;
D O I：
10.1017/S1471068421000260
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
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.
引用
收藏
页码：543 / 556
页数：14
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