Cognitive Model Optimization with Parallel Genetic Algorithms

ISBN-13: 9783639167849 / Angielski / Miękka / 2009 / 108 str.

Sue Kase

Opis

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 fields 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.

O autorze

PhD, College of Information Sciences and Technology
at the Pennsylvania State University. Postdoctoral Fellow at the
Defense Threat Reduction Agency, Directorate of Basic and
Applied Science, Fort Belvoir, Virginia. Senior Modeling and
Simulation Engineer at The MITRE Corporation, McLean, Virginia.