Large language models are in-context semantic reasoners rather than symbolic reasoners
The emergent few-shot reasoning capabilities of Large Language Models (LLMs) have
excited the natural language and machine learning community over recent years. Despite of …
excited the natural language and machine learning community over recent years. Despite of …
[PDF][PDF] Problog: A probabilistic prolog and its application in link discovery.
We introduce ProbLog, a probabilistic extension of Prolog. A ProbLog program defines a
distribution over logic programs by specifying for each clause the probability that it belongs …
distribution over logic programs by specifying for each clause the probability that it belongs …
Probabilistic (logic) programming concepts
A multitude of different probabilistic programming languages exists today, all extending a
traditional programming language with primitives to support modeling of complex, structured …
traditional programming language with primitives to support modeling of complex, structured …
[كتاب][B] Foundations of Probabilistic Logic Programming: Languages, semantics, inference and learning
F Riguzzi - 2023 - taylorfrancis.com
Since its birth, the field of Probabilistic Logic Programming has seen a steady increase of
activity, with many proposals for languages and algorithms for inference and learning. This …
activity, with many proposals for languages and algorithms for inference and learning. This …
On the implementation of the probabilistic logic programming language ProbLog
The past few years have seen a surge of interest in the field of probabilistic logic learning
and statistical relational learning. In this endeavor, many probabilistic logics have been …
and statistical relational learning. In this endeavor, many probabilistic logics have been …
[كتاب][B] Foundations of fuzzy logic and semantic web languages
U Straccia - 2013 - library.oapen.org
This book is the first to combine coverage of fuzzy logic and Semantic Web languages. It
provides in-depth insight into fuzzy Semantic Web languages for non-fuzzy set theory and …
provides in-depth insight into fuzzy Semantic Web languages for non-fuzzy set theory and …
Structure learning of probabilistic logic programs by searching the clause space
Learning probabilistic logic programming languages is receiving an increasing attention,
and systems are available for learning the parameters (PRISM, LeProbLog, LFI-ProbLog …
and systems are available for learning the parameters (PRISM, LeProbLog, LFI-ProbLog …
The magic of logical inference in probabilistic programming
Today, there exist many different probabilistic programming languages as well as more
inference mechanisms for these languages. Still, most logic programming-based languages …
inference mechanisms for these languages. Still, most logic programming-based languages …
A history of probabilistic inductive logic programming
The field of Probabilistic Logic Programming (PLP) has seen significant advances in the last
20 years, with many proposals for languages that combine probability with logic …
20 years, with many proposals for languages that combine probability with logic …
A survey in indexing and searching XML documents
XML holds the promise to yield (1) a more precise search by providing additional information
in the elements,(2) a better integrated search of documents from heterogeneous sources,(3) …
in the elements,(2) a better integrated search of documents from heterogeneous sources,(3) …