Neurosymbolic AI: Combining Neural Networks with Symbolic Reasoning

Abstract — Neurosymbolic AI is an emerging field that integrates the strengths of neural networks and symbolic reasoning to create interpretable, generalizable, and efficient AI systems. Neural networks excel at pattern recognition but lack transparency, while symbolic reasoning provides logical structure but lacks flexibility. By combining these two paradigms, neurosymbolic AI enables systems that can both learn from raw data and apply rule-based reasoning. This paper discusses foundational concepts, integration approaches, applications across NLP, robotics, and healthcare, and future research directions including symbolic rule learning, explainability, and end-to-end model integration.