Article Dans Une Revue Neural Computing and Applications Année : 2024

Neuro-symbolic artificial intelligence: a survey

Résumé

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.

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Dates et versions

hal-04603154 , version 1 (12-06-2024)

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Bikram Pratim Bhuyan, Amar Ramdane-Cherif, Ravi Tomar, T P Singh. Neuro-symbolic artificial intelligence: a survey. Neural Computing and Applications, 2024, pp.1-36. ⟨10.1007/s00521-024-09960-z⟩. ⟨hal-04603154⟩
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