It has long been recognized that in order to build a good system in which a person and a machine cooperate to perform a task it is important to take into account some significant characteristics of people. These characteristics are used to build some kind of a "user model". Traditionally, the model that is built is a model of a canonical (or typical) user. But often individual users vary so much that a model of a canonical user is insufficient. Instead, models of individual users are necessary. This article presents some examples of situations in which individual user models are important. It also presents some techniques that make the construction and use of such models possible. These techniques all reflect a desire to place most of the burden of constructing the models on the system, rather than on the user. This leads to the development of models that are collections of good guesses about the user. Thus some kind of probabilistic reasoning is necessary. And as the models are being used to guide the underlying system, they must also be monitored and updated as suggested by the interactions between the user and the system. The performance of one system that uses some of these techniques is discussed. 1.

Highway Traffic Safety Administration, in the interest of information exchange. The opinions, findings, and conclusions expressed in this publication are those of the authors and not necessarily those of the Department of Transportation or the National Highway Traffic Safety Administration. The United States Government assumes no liability for its contents or use thereof. If trade names, manufacturers’ names, or specific products are mentioned, it is because they are considered essential to the object of the publication and should not be construed as an endorsement. The United States Government does not endorse products or manufacturers. 1. Report No. DOT HS 811 091

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