Name
Abstract | ||
|---|---|---|
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 propo- sitional 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. |
Year | DocType | Citations |
|---|---|---|
2009 | Conference | 0 |
PageRank | References | Authors |
0.34 | 8 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Oliver Ray | 1 | 171 | 13.02 |
| bruno golenia | 2 | 0 | 0.34 |