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Analysis Of Genotype Size For An Evolvable Hardware System

Authors: Stomeo, E; Kalganova, T; Lambert, C;

Analysis Of Genotype Size For An Evolvable Hardware System

Abstract

{"references": ["X. Yao, T. Higuchi; \"Promises and challenges of evolvable hardware\"\nIEEE Trans. Systems, Man and Cybernetics, Part C, volume 29, pp. 87 -\n97, February 1999.", "H. de Garis. \"Evolvable Hardware: Principles and Practice\".\nCommunications of the Association for Computer Machinery (CACM\nJournal). August 1997.", "J.D. Lohn, D.S. Linden, G.S. Hornby, W.F. Kraus, A. Rodriguez-\nArroyo, S.E. Seufert. \"Evolutionary design of an X-band antenna for\nNASA's space technology 5 mission\". NASA/DoD Conference on\nEvolvable Hardware, 2003.Page(s):155 - 163.", "S. V. Hum, M. Okoniewski, R. J. Davies. \"An Evolvable Antenna\nPlatform Based on Reconfigurable Reflectarrays\". The 2005 NASA/DoD\nConference on Evolvable Hardware. June 29 - July 1, 2005, Washington\nDC, USA. IEEE Computer Society. Pages 139 - 146.", "E. Stomeo and T. Kalganova. \"Improving EHW performance\nintroducing a new decomposition strategy\". 2004 IEEE Conference on\nCybernetics and Intelligent Systems. Singapore 1-3 December 2004.\nPublisher IEEE Inc., New York, NY 10016-5997, United States. Pages\n439-444.", "E. Stomeo, T. Kalganova, C. Lambert, N. Lipnitsakya, Y. Yatskevich.\n\"On Evolution of Relatively Large Combinational Logic Circuits\". The\n2005 NASA/DoD Conference on Evolvable Hardware. June 29 - July 1,\n2005, Washington DC, USA. IEEE Computer Society. Pages 59 - 66.", "S.Zhao, L. Jiao, Y. Wang. \"Evolutionary Design of Analog Circuits with\na Uniform Design Based Multi-Objective Adaptive Genetic Algorithm\".\nThe 2005 NASA/DoD Conference on Evolvable Hardware. June 29 -\nJuly 1, 2005, Washington DC, USA. IEEE Computer Society. Pages 26\n- 29.", "A.H. Aguirre, R. Zebulum, C. Coello Coello. \"Evolutionary\nmultiobjective design targeting a Field Programmable Transistor Array\".\nNASA/DoD Conference on Evolvable Hardware, 2004. 24-26 June 2004\nPage(s):199 - 205.", "A. Stoica, D. Keymeulen, T. Arslan, Vu Duong, R. Zebulum, I.\nFerguson, Xin Guo \"Circuit self-recovery experiments in extreme\nenvironments\". NASA/DoD Conference on Evolvable Hardware, 2004.\n24-26 June 2004 Page(s):142 - 145.\n[10] A. M. Tyrrell, R. A. Krohling and Y. Zhou. \"Evolutionary algorithm for\nthe promotion of evolvable hardware\". Computers and Digital\nTechniques, IEE Proceedings- Volume 151, Issue 4, 18 July 2004\nPage(s):267 - 275.\n[11] D. E. Goldberg. Genetic algorithm in search, optimization and machine\nlearning. Addison-Wesley Publishing Company, Incorporated, Reading,\nMassachusetts, 1989.\n[12] J. Holland. Adaptation in Natural and Artificial Systems. Ann Arbor,\nMI: University of Michigan Press, 1975.\n[13] M. D. Vose. \"The Simple Genetic Algorithm\". MA: MIT Press 1999.\n[14] Jim Torresen. \"Two-Step Incremental Evolution of a Prosthetic Hand\nController Based on Digital Logic Gates\". 4th Int. Conf. on Evolvable\nHardware (ICES2001), October 2001, Tokyo, Japan.\n[15] P. Andersen. Evolvable Hardware: Artificial Evolution of Hardware\nCircuits in Simulation and Reality, M.Sc. Thesis, University of Aarhus,\nDenmark.\n[16] Timothy G. W. Gordon and Peter J. Bentley. \"On Evolvable Hardware\".\nIn Ovaska, S. and Sztandera, L. (Ed.) Soft Computing in Industrial\nElectronics. Physica-Verlag, Heidelberg, Germany, pp. 279-323.\n[17] A. Stoica, R. Zebulum, and D. Keymeulen, \"Mixtrinsic evolution,\" in\nInternational Conference on Evolvable Systems, Edinburgh, U.K., Apr.\n2000, pp. 208-217.\n[18] T. Kalganova and J. Miller. \"Evolving more efficient digital circuits by\nallowing circuit layout evolution and multi-objective fitness\".\nProceedings of the First NASA/DoD Workshop on Evolvable Hardware,\n19-21 July 1999 Page(s):54 - 63.\n[19] Jim Torresen. \"Evolving Multiplier Circuits by Training Set and\nTraining Vector Partitioning\". In proc. of Fifth International Conference\non Evolvable Hardware (ICES03), Springer LNCS 2606, pp. 228-237,\nMarch 2003, Trondheim, Norway.\n[20] Higuchi, T.; Iwata, M.; Keymeulen, D.; Sakanashi, H.; Murakawa, M.;\nKajitani, I.; Takahashi, E.; Toda, K.; Salami, N.; Kajihara, N.; Otsu, N.;\n\"Real-world applications of analog and digital evolvable hardware\"\nIEEE Transactions on Evolutionary Computation , Vol.: 3 Issue: 3 ,\nSept. 1999 Page(s): 220 -235.\n[21] J. Miller. \"An empirical study of the efficiency of learning Boolean\nfunctions using a Cartesian genetic programming approach\" In Proc. of\nthe Genetic and Evolutionary Computation Conference, volume 1, pp.\n1135-1142, Orlando, USA, July 1999.\n[22] J. F. Miller and P. Thomson. \"Cartesian genetic programming\". In\nRiccardo Poli, Wolfgan Banzhaf, William B. Langdon, Julian F. Miller,\nPeter Nordin and Terence C. Forgaty, editors. Genetic Programming,\nProceedings of EuroGP 2000. Vol. 1802 of LNCS, pages 121-132,\nEdinburg, 16 April 2000. Springer-Verlag."]}

The evolution of logic circuits, which falls under the heading of evolvable hardware, is carried out by evolutionary algorithms. These algorithms are able to automatically configure reconfigurable devices. One of main difficulties in developing evolvable hardware with the ability to design functional electrical circuits is to choose the most favourable EA features such as fitness function, chromosome representations, population size, genetic operators and individual selection. Until now several researchers from the evolvable hardware community have used and tuned these parameters and various rules on how to select the value of a particular parameter have been proposed. However, to date, no one has presented a study regarding the size of the chromosome representation (circuit layout) to be used as a platform for the evolution in order to increase the evolvability, reduce the number of generations and optimize the digital logic circuits through reducing the number of logic gates. In this paper this topic has been thoroughly investigated and the optimal parameters for these EA features have been proposed. The evolution of logic circuits has been carried out by an extrinsic evolvable hardware system which uses (1+λ) evolution strategy as the core of the evolution.

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Keywords

Computational intelligence, computational intelligence, design of logic circuits., Genotype size, Evolvable hardware, genotype size, Design of logic circuits

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