Leonie March

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One feature of intelligent user interfaces is an ability to make decisions that take into account a variety of factors, some of which may depend on the current situation. This article focuses on one general approach to such decision making: Predict the consequences of possible system actions on the basis of prior empirical learning, and evaluate the(More)
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(More)
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