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Trustworthy decision-making via symbolic logic and neural networks

Combine symbolic logic with neural networks to ensure reliable and trustworthy decision-making in Neuro-Symbolic AI, explicitly addressing consistency and robustness of decisions.

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Background

The review notes efforts to integrate neural flexibility with symbolic precision. The authors explicitly identify as open the challenge of combining symbolic logic and neural models to guarantee trustworthy decision-making.

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