Abstract
In this paper, we propose a new modification of Cartesian Genetic Programming (CGP) that enables to optimize digital circuits more significantly than standard CGP. We argue that considering fully functional but not necessarily smallest-discovered individual as the parent for new population can decrease the number of harmful mutations and so improve the search space exploration. This phenomenon was confirmed on common benchmarks such as combinational multipliers and the LGSynth91 circuits.
Keywords
- Digital Circuit
- Parent Individual
- Cartesian Genetic Programming
- Conventional Synthesis
- Correct Individual
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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References
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Gajda, Z., Sekanina, L. (2010). An Efficient Selection Strategy for Digital Circuit Evolution. In: Tempesti, G., Tyrrell, A.M., Miller, J.F. (eds) Evolvable Systems: From Biology to Hardware. ICES 2010. Lecture Notes in Computer Science, vol 6274. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15323-5_2
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DOI: https://doi.org/10.1007/978-3-642-15323-5_2
Publisher Name: Springer, Berlin, Heidelberg
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