PAL Boot Camp: Preparing Cognitive Assistants for Deployment
Author
Lange, Douglas S.
Carlin, Michael
Ivanchenko, Volodymyr
Berzins, Valdis
Luqi
Date
2007Metadata
Show full item recordAbstract
Most visions for decision support and information technology anticipate the use of machine learning to enable software to
respond to an adapting environment, including the ability to learn capabilities while on-the-job. Currently, systems and
software engineering processes hinder employment of task learning technology, because the adaptation it provides runs
counter to our notions of stability. Similarly, systems must typically demonstrate satisfaction of requirements before
deployment, rather than learn tasks while on the job. This paper introduces new problems for the field of software
engineering and discusses an approach for preparing cognitive systems for deployment. We describe one approach to a boot
camp for cognitive systems and present the results of simulations of the boot camp. The results of our experiments provide
thresholds and patterns for knowledge, and the requirement for specific patterns of human use of cognitive systems. These
results are then used to infer requirements for a boot camp and measures for the prediction of successful employment of the
assistant.
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This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.Collections
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