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Human performance modeling for system of systems analytics.
Author(s) -
Kevin R. Dixon,
Craig R. Lawton,
Justin Basilico,
Dennis E. Longsine,
James C. Forsythe,
John H. Gauthier,
Hai D. Le
Publication year - 2008
Publication title -
osti oai (u.s. department of energy office of scientific and technical information)
Language(s) - English
Resource type - Reports
DOI - 10.2172/971414
Subject(s) - computer science , interim , cognition , systems modeling , cognitive model , analytics , human–computer interaction , data science , artificial intelligence , machine learning , software engineering , psychology , archaeology , neuroscience , history
A Laboratory-Directed Research and Development project was initiated in 2005 to investigate Human Performance Modeling in a System of Systems analytic environment. SAND2006-6569 and SAND2006-7911 document interim results from this effort; this report documents the final results. The problem is difficult because of the number of humans involved in a System of Systems environment and the generally poorly defined nature of the tasks that each human must perform. A two-pronged strategy was followed: one prong was to develop human models using a probability-based method similar to that first developed for relatively well-understood probability based performance modeling; another prong was to investigate more state-of-art human cognition models. The probability-based modeling resulted in a comprehensive addition of human-modeling capability to the existing SoSAT computer program. The cognitive modeling resulted in an increased understanding of what is necessary to incorporate cognition-based models to a System of Systems analytic environment

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