| Sushil J. Louis. Working from blueprints: Evolutionary learning for design. Artificial Intelligence in Engineering, 11(3):335--341, 1997. |
....methods implicitly allows the GA to vary the thresh15 old of acceptability over the course of the search, and makes a much weaker assumption about the shape of the boundary between good and bad regions than is the case for other learning methods. Also in the field of GA design optimization [ Louis 1997 ] presented a method for using information about an entire GA optimization to guide other GA optimizations in similar domains. Several research e#orts outside the GA field also focused on the idea of using search history to guide future exploration. The examples include: Tabu search [ Glover ....
Sushil J. Louis. Working from blueprints: Evolutionary learning for design. Artificial Intelligence in Engineering, 11(3):335--341, 1997.
....implicitly allows the GA to vary the threshold of acceptability over the course of the search, and makes a much weaker assumption about the shape of the boundary between good and bad regions than is the case for traditional inductive learning methods. Also in the field of GA optimization [ Louis 1997 ] presented a method for using information about an entire GA optimization to guide another GA optimization in a similar domain. He presented his work in a design optimization framework. Several research efforts outside the GA field also focused on the idea of using search history to guide future ....
Sushil J. Louis. Working from blueprints: Evolutionary learning for design. Artificial Intelligence in Engineering, 11(3):335--341, 1997.
No context found.
Louis, S. Working from blueprints: evolutionary learning for design, ???DETAILS FROM THIS ISSUE???
Online articles have much greater impact More about CiteSeer.IST Add search form to your site Submit documents Feedback
CiteSeer.IST - Copyright Penn State and NEC