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Learning rules from user behaviour

Corapi, Domenico; Ray, Oliver; Russo, Alessandra; Bandara, Arosha and Lupu, Emil (2009). Learning rules from user behaviour. In: Artificial Intelligence Applications and Innovations III: Proceedings of the 5TH IFIP Conference on Artificial Intelligence Applications and Innovations (AIAI '2009), 23-25 April 2009, Thessaloniki, Greece, pp. 459–468.

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DOI (Digital Object Identifier) Link: https://doi.org/10.1007/978-1-4419-0221-4_54
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Abstract

Pervasive computing requires infrastructures that adapt to changes in user behaviour while minimising user interactions. Policy-basedapproaches have been proposed as a means of providing adaptability but, at present, require policy goals and rules to be explicitly defined by users. This paper presents a novel, logic-based approach for automatically learning and updating models of users
from their observed behaviour. We show how this task can be accomplished using a nonmonotonic learning system, and we illustrate how the approach can be exploited within a pervasive computing framework.

Item Type: Conference Item
Copyright Holders: 2009 The Authors
Academic Unit/Department: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Interdisciplinary Research Centre: Centre for Policing Research and Learning (CPRL)
Centre for Research in Computing (CRC)
Item ID: 18781
Depositing User: Arosha Bandara
Date Deposited: 02 Nov 2009 09:29
Last Modified: 12 Nov 2016 12:49
URI: http://oro.open.ac.uk/id/eprint/18781
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