Neuro Symbolic Learning with Differentiable Inductive Logic Programming

Paulo Shakarian, Chitta Baral, Gerardo I. Simari, Bowen Xi, Lahari Pokala

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

In this chapter, we describe how a logic program can be learned from data in a neuro symbolic framework. Our focus is on the gradient-based method known as differentiable inductive logic programming (ILP), which combines concepts from ILP with a neural architecture to support gradient-based learning. Additionally, we also cover several other paradigms to learn logical structures in a neuro symbolic framework.

Original languageEnglish (US)
Title of host publicationSpringerBriefs in Computer Science
PublisherSpringer
Pages75-87
Number of pages13
DOIs
StatePublished - 2023

Publication series

NameSpringerBriefs in Computer Science
VolumePart F1425
ISSN (Print)2191-5768
ISSN (Electronic)2191-5776

ASJC Scopus subject areas

  • General Computer Science

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