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Explanations are central to causal reasoning, and cognitive science has long established that the human drive to explain is itself a mechanism for learning about causality. Despite this, learning from those abductive signals is largely ignored in artificial intelligence. While explainable AI (XAI) increasingly draws on...
Constrained-guided mapping is proposed, a neuro-symbolic method with three stages: schema-grounded admissibility constraints with metadata mc =, where tau_c denotes the constraint type and delta_c provides executable relation and normalization logic, and constraint-restricted candidate generation with cascade relaxatio...
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