The RAIL Principles for Neurosymbolic AI: Reasoning, Assurances, Interfacing and Learning

City Research Online (City University London) · 2026-11-06 · 期刊论文

Neurosymbolic AI systems that integrate machine learning and symbolic reasoning are rapidly gaining attention. They complement the data-intensive statistical approaches of neural networks and language models with symbolic reasoning formalism and algorithms to function in high-stakes domains or in low-data regimes that characterize many real-world applications. We argue that the neurosymbolic combination of machine le…

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A. d'Avila Garcez

本文摘自《每日前沿研究简报 · 2026-11-06》「AI 科研智能体 / AI 科学家」。本内容仅用于研究信息整理与科普交流，不构成医疗建议。