Argumentation neural networks

Artur D'Avila Garcez, Dov Gabbay, Luis C. Lamb

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

2 Scopus citations

Abstract

While neural networks have been successfully used in a number of machine learning applications, logical languages have been the standard for the representation of legal and argumentative reasoning. In this paper, we present a new hybrid model of computation that allows for the deduction and learning of argumentative reasoning. We propose a Neural Argumentation Algorithm to translate argumentation networks into standard neural networks, and prove correspondence between the semantics of the two networks.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsNikhil R. Pal, Srimanta Pal, Nikola Kasabov, Rajani K. Mudi, Swapan K. Parui
PublisherSpringer Verlag
Pages606-612
Number of pages7
ISBN (Print)3540239316, 9783540239314
DOIs
StatePublished - 2004
Externally publishedYes

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3316
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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