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Learning from Experience: Case Injected Genetic Algorithm Design of Combinational Logic Circuits

  • Sushil J. Louis

Abstract

This paper presents a new approach to genetic algorithm based design. We use genetic algorithms augmented with a case-based memory of past design problem solving attempts to obtain better performance over time on sets of similar design problems. Rather than starting anew on each design, we periodically inject a genetic algorithm’s population with appropriate intermediate design solutions to similar, previously solved problems. Experimental results on a configuration design problem; the design of a parity checker circuit, demonstrate the performance gains from our approach and show that our system learns to take less time to provide quality solutions to a new design problem as it gains experience from solving other similar design problems.

Keywords

Genetic Algorithm Design Problem Boolean Function Parity Checker Injection Strategy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London 2002

Authors and Affiliations

  1. 1.Dept. of Computer ScienceUniversity of NevadaRenoUSA

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