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<p>Guaranteeing transparent and trustworthy AI behavior in safety–critical systems—autonomous vehicles, diagnostic healthcare, and industrial control—has now reached an urgent level of necessity. This paper puts forth a hybrid neuro-symbolic learning architecture that marries the statistical prowess of neural representation with the logical clarity of symbolic reasoning.</p>

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Hybrid Neuro-Symbolic Learning Framework for Explainable Decision-Making in Safety-Critical AI Systems

  • 期刊论文

  • 发表日期：

    2026年5月2日

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  • Pranjali Deshmukh,
  • Tejal Irkhede

摘要

Guaranteeing transparent and trustworthy AI behavior in safety–critical systems—autonomous vehicles, diagnostic healthcare, and industrial control—has now reached an urgent level of necessity. This paper puts forth a hybrid neuro-symbolic learning architecture that marries the statistical prowess of neural representation with the logical clarity of symbolic reasoning.