Neuro-symbolic AI has been an extensively studied model in the field of artificial intelligence, which combines learning from neural network statistics with the symbolic features of artificial intelligence. The purpose of this paper is to systematically study and analyse the existing research on NeSy AI, understanding its foundational concepts, approach, and domains. The research aims to synthesize a review-based approach that analyses existing results to determine how the neurolearning and symbolic approaches are integrated. The paper's significant findings state that NeSy AI enhances the capabilities of existing deep learning neural networks by providing a sense of reasoning or explainability in their decisions. It provides comparative data to analyse how NeSy AI is advantageous across various domains and sectors of society. Improving accuracy has been central to the results, with variations demonstrating a broader understanding of data and decision-making, and greater explainability. This paper also throws light on the different challenges that exist, including those linked to the adaptability, design, and utility of domain-focused rules and regulations.
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A Comprehensive Review of Neuro-Symbolic AI in Multi-Domain Integration
Semantic Scholar · 2026
Abstract
Neuro-symbolic AI has been an extensively studied model in the field of artificial intelligence, which combines learning from neural network statistics with the symbolic features of artificial intelligence. The purpose of this paper is to systematically study and analyse the existing research on NeSy AI, understanding its foundational concepts, approach, and domains. The research aims to synthesize a review-based approach that analyses existing results to determine how the neurolearning and symbolic approaches are integrated. The paper's significant findings state that NeSy AI enhances the capabilities of existing deep learning neural networks by providing a sense of reasoning or explainability in their decisions. It provides comparative data to analyse how NeSy AI is advantageous across various domains and sectors of society. Improving accuracy has been central to the results, with variations demonstrating a broader understanding of data and decision-making, and greater explainability. This paper also throws light on the different challenges that exist, including those linked to the adaptability, design, and utility of domain-focused rules and regulations.