A Neural Network Approach for First-Order Abductive Inference

Oliver Ray, Bruno Golenia, A Neural Network Approach for First-Order Abductive Inference. IJCAI09 Workshop on Neural-Symbolic Learning and Reasoning. July 2009. PDF, 259 Kbytes.


This paper presents a neural network approach for first-order abductive inference by generalising an existing method from propositional logic to the first-order case. We show how the original propositional method can be extended to enable the grounding of a first-order abductive problem; and we also show how it can be modified to allow the prioritised computation of minimal solutions. We illustrate the approach on a well-known abductive problem and explain how it can be used to perform first-order conditional query answering.

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