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. In this paper, we propose a case-based reasoning scheme in which we extract domain knowledge (in the form of design patterns) from a genetic algorithm used to optimize combinational logic circuits at the gate level. Such information is used in two ways: first, we show how the selection pressure of the genetic algorithm is biased by Boolean simplification rules that are normally adopted by human...
This paper investigates the effect of injection percentage on the performance of a case-injected genetic algorithm for combinational logic design. A case-injected genetic algorithm is a genetic algorithm augmented with a case-based memory of past problem solving attempts which learns to improve performance on sets of similar design problems. In this approach, rather than starting anew on each design,...
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