Scott M. Brown

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The complexity of current computer systems and software warrants research into methods to decrease the cognitive load on users. Determining how to get the right information into the right form with the right tool at the right time has become a monumental task | one necessitating intelligent interfaces agents with the ability to predict the users' needs or(More)
An underlying problem of current interface agent research is the failure to adequately address eeective and eecient knowledge representations and associated methodologies suitable for modeling the users' interactions with the system. These user models lack the representational complexity to manage the uncertainty and dynamics involved in predicting user(More)
The complexity of" current soft.ware applications is overwhelming users. The need exists for inteUigent interface agents to address the problems of increasing taskload that is overwhelming the hunloax user. Interface agents could help alleviate user taskload by extracting and analyzing relevant information, and providing information abstractions of that(More)
The PESKI (Probabilities, Expert Systems, Knowledge , and Inference) system attempts to address some of the problems in expert system design through the use of the Bayesian Knowledge Base (BKB) representation. Knowledge gathered from a domain expert is placed into this framework and inferencing under uncertainty is performed over it. However, by the nature(More)
This paper provides insight into combining stochastic and deterministic search methods using evolutionary algorithms (EAs) such as evolutionary programming, evolutionary strategies, and genetic algorithms integrated with depth-rst search with backtracking, branch and bound, and best-rst search algorithms such as A. An important view of such an integration(More)
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