Situations, the semantic interpretations of context, provide a better basis for selecting adaptive behaviours than context itself. The definition of situations typically rests on the ability to define logical expressions and inference methods to identify particular situations. In this paper we extend this approach to provide for efficient organisation and selection in systems with large numbers of situations having structured relationships to each other. We apply lattice theory to define a specialisation relationship across situations, and show how this can be used to improve the identification of situations using lattice operators and uncertain reasoning. We demonstrate the technique against a real-world dataset.
History
Publication title
Revue d'Intelligence Artificielle
Volume
22
Issue
5
Pagination
647-667
ISSN
0992-499X
Publisher
Lavoisier
Place of publication
14 rue de Provigny Cachan Cedex 94236 France
Repository Status
Restricted
Socio-economic Objectives
Information systems, technologies and services not elsewhere classified