Data Abstraction for Cognitive Models of Compositional Design in Genetic Algorithms

نویسندگان

  • Mary Elizabeth Kurz
  • James Peterson
چکیده

In this paper, we discuss the design of suites of equally valid optimization strategies for job scheduling using genetic algorithms. Our initial designs will be neutral in the sense that none of our choices lead to job schedules which when implemented would be described by qualities such as contented, antagonistic or demoralized. The data will provide training examples for meta level associative cortex and abstract emotion modules. There are two goals to this research: first, model the process of optimization design for eventual use in the development of an autonomous optimization scheduling program which is capable of using intangible qualities as part of the design process; and second, use the optimization model as a quantitative means of training the associative cortex portion and associated emotional circuits of a general model of cognition. ∗Department of Industrial Engineering, email: [email protected] †Department of Mathematical Sciences, email: [email protected]

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تاریخ انتشار 2003