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.
CITATION STYLE
Louis, S. J. (2002). Learning from Experience: Case Injected Genetic Algorithm Design of Combinational Logic Circuits. In Adaptive Computing in Design and Manufacture V (pp. 295–306). Springer London. https://doi.org/10.1007/978-0-85729-345-9_25
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