Scott M. Brown

Learn More
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)
Military and domestic security analysts and planners are facing threats whose asymmetric nature will sharply increase the challenges of establishing an adversary's intent. This complex environment will severely limit the capabilities of the classic doctrinal approach to diagnose adversary activity. Instead, a more dynamic approach is required-adversary(More)
Approved for public release; distribution unlimited The views expressed in this dissertation are those of the author and do not reeect the oocial policy or position of the Department of Defense or the United States Government. Acknowledgements I must foremost thank God for his unending patience and love. It was said to me while at AFIT the Lord does not(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)
Knowledge elicitation/acquisition continues to be a bottleneck to constructing decision-theoretic systems. Methodologies and techniques for incremental elicitation/acquisition of knowledge especially under uncertainty in support of users' current goals is desirable. This paper presents PESKI, a probabilistic expert system development environment. PESKI(More)
This paper reports our preliminary design and implementation towards the development of Kavanah, a system to help users retrieve information and discover knowledge for a medical domain application. The goal of this system is to adaptively react to the dynamic changes in the user's interests and preferences in searching for information within the context of(More)
Applications that have access to user intent and task context can support better, faster decision-making on the part of the user. In this paper, we present AUTOS, an approach to the implementation of individual and team intent inference. AUTOS uses observable contextual clues to infer current operator task state and predict future task state. Guided by the(More)