Design optimization using dynamic evaluation

  • Authors:
  • Witold Paluszynski;Ira Kalet

  • Affiliations:
  • University of Washington, Computer Science Department, Seattle, WA;University of Washington, Radiation Oncology Department, Seattle, WA

  • Venue:
  • IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
  • Year:
  • 1989

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Abstract

We describe a search strategy that may be useful for a class of design problems by developing an example from cancer radiation treatment planning. This application problem involves typical features of design problems such as constraints, optimality, a large search space with continuously varying parameters as well as discrete (non-numeric) parameters. There is no known method of comparing elements of the solution space based on a static evaluation function. We have therefore developed a dynamic evaluation function, which attempts to heuristically compare all solutions with one another, as a way of interpreting the evaluation results. This allows us to use an analog of hill-climbing with a simple SELECT-GENERATE-TEST loop where expert rules are used as "move generators" and a similarity metric is used to control or direct the application of the rules for plan modification. Preliminary tests of these ideas indicate that a practical working system can be built.