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Scalable integration of logic programming and neural networks

Develop scalable frameworks that integrate traditional logic programming with neural networks to support complex reasoning tasks in Neuro-Symbolic AI.

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Background

The survey highlights systems that blend probabilistic logic, neural components, and logic programming for reasoning. The authors explicitly mention that scaling such integrated frameworks for complex tasks remains open.

References

Open research questions remain around how Neuro-Symbolic AI can develop scalable frameworks that integrate traditional logic programming with neural networks for complex reasoning tasks, incorporate commonsense knowledge and advanced language understanding to enhance multi-hop reasoning capabilities, combine symbolic logic with neural networks to ensure reliable and trustworthy decision-making and integrate meta-cognitive abilities to enable self-monitoring and adjustment of reasoning strategies for clearer, more understandable explanations.

— Neuro-Symbolic AI in 2024: A Systematic Review (2501.05435 - Colelough et al., 9 Jan 2025) in Section 4.4 Logic and Reasoning