Creating an empirical basis for adaptation decisions

Authors:
Anthony Jameson;Barbara Großmann-Hutter;Leonie March;Ralf Rummer
Affiliations:
Department of Computer Science/Department of Psychology, University of Saarbrücken, P.O. Box 15 11 50, 66041 Saarbrücken, Germany;Department of Computer Science/Department of Psychology, University of Saarbrücken, P.O. Box 15 11 50, 66041 Saarbrücken, Germany;Department of Computer Science/Department of Psychology, University of Saarbrücken, P.O. Box 15 11 50, 66041 Saarbrücken, Germany;Department of Computer Science/Department of Psychology, University of Saarbrücken, P.O. Box 15 11 50, 66041 Saarbrücken, Germany
Venue:
Proceedings of the 5th international conference on Intelligent user interfaces
Year:
2000

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Abstract

How can an adaptive intelligent interface decide what particular action to perform in a given situation, as a function of perceived properties of the user and the situation? Ideally, such decisions should be made on the basis of an empirically derived causal model. In this paper we show how such a model can be constructed given an appropriately limited system and domain: On the basis of data from a controlled experiment, an influence diagram for making adaptation decisions is learned automatically. We then discuss why this method will often be infeasible in practice, and how parts of the method can nonetheless be used to create a more solid basis for adaptation decisions.