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Neuro-symbolic artificial intelligence: a survey.

Authors :
Bhuyan, Bikram Pratim
Ramdane-Cherif, Amar
Tomar, Ravi
Singh, T. P.
Source :
Neural Computing & Applications. Jun2024, p1-36.
Publication Year :
2024

Abstract

The goal of the growing discipline of neuro-symbolic artificial intelligence (AI) is to develop AI systems with more human-like reasoning capabilities by combining symbolic reasoning with connectionist learning. We survey the literature on neuro-symbolic AI during the last two decades, including books, monographs, review papers, contribution pieces, opinion articles, foundational workshops/talks, and related PhD theses. Four main features of neuro-symbolic AI are discussed, including representation, learning, reasoning, and decision-making. Finally, we discuss the many applications of neuro-symbolic AI, including question answering, robotics, computer vision, healthcare, and more. Scalability, explainability, and ethical considerations are also covered, as well as other difficulties and limits of neuro-symbolic AI. This study summarizes the current state of the art in neuro-symbolic artificial intelligence. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09410643
Database :
Academic Search Index
Journal :
Neural Computing & Applications
Publication Type :
Academic Journal
Accession number :
177689881
Full Text :
https://doi.org/10.1007/s00521-024-09960-z