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arXiv · 2610.07313

Rule-Based Languages for Neurosymbolic AI

Stefania Dumbrava·Efthymia Tsamoura
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Abstract

Logic programming is increasingly used as the symbolic component of neurosymbolic AI systems. We survey the main rule-based languages in this setting, namely Datalog, answer set, and probabilistic logic programs, along four axes: semantics, expressiveness, neural integration, and evaluation mechanism. We analyse over 50 recent systems and applications, comparing formalism usage across four research areas: databases and programming languages, machine learning, vision, and robotics. We provide a decision matrix mapping application scenarios to required features and close by outlining open problems.

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Stefania Dumbrava, Efthymia Tsamoura. 2026-10-05. Rule-Based Languages for Neurosymbolic AI. https://arxiv.org/abs/2610.07313

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