Abstract
This paper shows how automated abduction
and induction can be used to infer logical
process models from temporal observations
of states and actions. The proposed method
employs a non-monotonic learning system
called eXtended Hybrid Abductive Inductive
Learning (XHAIL) to learn domain axioms
in a temporal logic programming formalism
known as the Event Calculus (EC). The key
benefit of this logical learning method is its
ability to utilise background knowledge and
to return human understandable hypotheses.
The approach is illustrated on a simplified
biological process modelling task.
| Translated title of the contribution | Inferring process models from temporal data with abduction and induction |
|---|---|
| Original language | English |
| Title of host publication | 1st International Workshop on the Induction of Process Models |
| Publication status | Published - 2007 |
Bibliographical note
Other page information: -Conference Proceedings/Title of Journal: 1st International Workshop on the Induction of Process Models
Other identifier: 2000827