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Cognitive Model Optimization with Parallel Genetic Algorithms
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To enable an individual differences investigation of §how stress affects cognitive performance in a mental §serial subtraction task a new optimization approach §was developed for computing the fit of a serial §subtraction cognitive model to human performance §data by varying architectural parameters. The new §optimization approach utilizes a modified parallel §genetic algorithm (PGA) on a high performance §computing (HPC) cluster together with the ACT-R §cognitive architecture and a serial subtraction §cognitive model. The optimization approach was §highly successful in fitting the serial subtraction §model superseding the field s traditional manual §optimization process. The optimization results §revealed several interesting patterns in the §parametric values found to produce best fits to the §human data; some of which are supported by §individual differences theories of stress and §anxiety from cognitive performance research. The §book describes a prototype optimization system for §individual differences modeling and validation that §is useful to cognitive science and performance §researchers.
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