← Back to Benchmarks
simmediumroboticsmetric · varies
World2Rules: A Neuro-Symbolic Framework for Learning World-Governing Safety Rules for Aviation
Description
Many real-world safety-critical systems are governed by explicit rules that define unsafe world configurations and constrain agent interactions. In practice, these rules are complex and context-dependent, making manual specification incomplete and error-prone. Learning such rules from real-world multimodal data is further challenged by noise, inconsistency, and sparse failure cases. Neural models can extract structure from text and visual data but lack formal guarantees, while symbolic methods p