Abductive inference has long been associated with the logic of scientific discovery and automated abduction is now being used in real scientific tasks. But few methods can exploit the full potential of clausal logic and abduce non-ground explanations with indefinite answers. This paper shows how the consequence finding method of Skip Ordered Linear (SOL) resolution can overcome the limitations of existing systems by proposing a method that is sound and complete for finding minimal abductive solutions under a variety of pruning mechanisms. Its utility is shown with an example based on metabolic network modelling.
|Translated title of the contribution||A Consequence Finding Approach for Full Clausal Abduction|
|Title of host publication||10th International Conference on Discovery Science|
|Publication status||Published - 2007|
Bibliographical noteOther page information: 173-184
Conference Proceedings/Title of Journal: 10th International Conference on Discovery Science
Other identifier: 2000825