Pervasive computing requires infrastructures that adapt to changes in user behaviour while minimising user interactions. Policy- based approaches provide adaptability but, at present, require policy rules to be provided by users. This paper presents preliminary work on using Inductive Logic Programming (ILP) to automatically acquire such knowledge from observational data. We show how a non-monotonic ILP system called XHAIL can incrementally learn and revise rules of user behaviour and we brie y discuss how this approach might be exploited within a wider pervasive computing framework.
|Translated title of the contribution||Learning Rules from User Behaviour|
|Title of host publication||2nd International Workshop on the Induction of Process Models|
|Publication status||Published - 2008|
Bibliographical noteOther page information: -
Conference Proceedings/Title of Journal: 2nd International Workshop on the Induction of Process Models
Other identifier: 2000965