Formal Models of Human Control and Interaction with CPS
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Computational simulation is one of the most im- portant ways of reproducing the dynamic responses of a Cyber Physical System using a model of the system. The simulation discovers areas of differential system performance and allows linking such performance back to system characteristics. In the medical domain, patient simulators are used to train physicians in patient management. One critical question is how to verify these systems under realistic human (physician) input. This requires the creation of realistic human models that would be able to capture human cognitive and decision abilities and lim- itations. Verification of such an overall physician-patient model would result in two advantages: (a) since physicians realistically would not give all possible inputs to the system, verification could be more efficient and (b) the verification may uncover areas of poor human performance. In this paper, we describe our methodology and results in creating a computational model of human fluid management in critical care, based on human experiments.
Submitted by Katia Sycara
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Computational simulation is one of the most im- portant ways of reproducing the dynamic responses of a Cyber Physical System using a model of the system. The simulation discovers areas of differential system performance and allows linking such performance back to system characteristics. In the medical domain, patient simulators are used to train physicians in patient management. One critical question is how to verify these systems under realistic human (physician) input. This requires the creation of realistic human models that would be able to capture human cognitive and decision abilities and lim- itations. Verification of such an overall physician-patient model would result in two advantages: (a) since physicians realistically would not give all possible inputs to the system, verification could be more efficient and (b) the verification may uncover areas of poor human performance. In this paper, we describe our methodology and results in creating a computational model of human fluid management in critical care, based on human experiments.