Results 231 to 240 of about 81,262 (253)

Probabilistic Inductive Logic Programming on the Web

2017
Probabilistic Inductive Logic Programming (PILP) is gaining attention for its capability of modeling complex domains containing uncertain relationships among entities. Among PILP systems, cplint provides inference and learning algorithms competitive with the state of the art. Besides parameter learning, cplint provides one of the few structure learning
RIGUZZI, Fabrizio, ZESE, Riccardo, COTA, Giuseppe   +2 more
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Learning the Structure of Probabilistic Logic Programs

2012
There is a growing interest in the field of Probabilistic Inductive Logic Programming, which uses languages that integrate logic programming and probability. Many of these languages are based on the distribution semantics and recently various authors have proposed systems for learning the parameters (PRISM, LeProbLog, LFI-ProbLog and EMBLEM) or both ...
BELLODI, Elena, RIGUZZI, Fabrizio
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Probabilistic Planning in Hybrid Probabilistic Logic Programs

2007
In this paper, we present a new approach to probabilistic planning based on logic programming, by relating probabilistic planning to hybrid probabilistic logic programs with probabilistic answer set semantics [32]. We show that any probabilistic planning problem, $\cal P$, can be translated into a hybrid probabilistic logic program whose probabilistic ...
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Deep probabilistic logic programming

2017
Probabilistic logic programming under the distribution semantics has been very useful in machine learning. However, inference is expensive so machine learning algorithms may turn out to be slow. In this paper we consider a restriction of the language called hierarchical PLP in which clauses and predicates are hierarchically organized.
NGUEMBANG FADJA, Arnaud, LAMMA, Evelina, RIGUZZI, Fabrizio   +2 more
openaire   +1 more source

Neural probabilistic logic programming in DeepProbLog

Artificial Intelligence, 2021
Robin Manhaeve, Sebastijan Dumancic, Angelika Kimmig   +2 more
exaly  

Abduction with probabilistic logic programming under the distribution semantics

International Journal of Approximate Reasoning, 2022
Damiano Azzolini, Elena Bellodi, Stefano Ferilli   +2 more
exaly  

Probabilistic Databases and Logic Programming

2001
Uncertainty occurs in the world in many ways. For instance, image processing programs identify the content of images with some levels of uncertainty. Prediction programs predict when events will occur with certain probabilities. In this tutorial, I will focus on probabilistic methods to handle uncertainty.
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Optochemical Control of DNA‐Switching Circuits for Logic and Probabilistic Computation

Angewandte Chemie - International Edition, 2021
Mingshu Xiao, Wei Lai, Li Li
exaly  

Toward Semantic Communication Protocols: A Probabilistic Logic Perspective

IEEE Journal on Selected Areas in Communications, 2023
Sejin Seo, Jihong Park, Seung-Woo Ko
exaly  

Probabilistic Logic Programming Languages

2022
openaire   +1 more source