1. Neuro-symbolic artificial intelligence: a survey.
- Author
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Bhuyan, Bikram Pratim, Ramdane-Cherif, Amar, Tomar, Ravi, and Singh, T. P.
- Subjects
- *
ARTIFICIAL intelligence , *KNOWLEDGE representation (Information theory) , *COMPUTER vision , *MACHINE learning , *ROBOTICS , *QUESTION answering systems - 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]
- Published
- 2024
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