Journal of KIISE:Software and Applications (한국정보과학회논문지:소프트웨어및응용)

Korean Institute of Information Scientists and Engineers (한국정보과학회)
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Increasing Diversity of Evolvable Hardware with Speciation Technique

종분화 기법을 이용한 진화 하드웨어의 다양성 향상

  • 황금성 (연세대학교 컴퓨터과학과) ;
  • 조성배 (연세대학교 컴퓨터과학과)
  • Published : 2005.01.01
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Abstract

Evolvable Hardware is the technique that obtains target function by adapting reconfigurable digital' devices to environment in real time using evolutionary computation. It opens the possibility of automatic design of hardware circuits but still has the limitation to produce complex circuits. In this paper, we have analyzed the fitness landscape of evolvable hardware and proposed a speciation technique of evolving diverse individuals simultaneously, proving the efficiency empirically. Also, we show that useful extra functions can be obtained by analyzing diverse circuits from the speciation technique.

진화 하드웨어(evolvable hardware)는 재구성 가능한 디지털 회로에 진화연산이 적용되어 실시간으로 환경에 적응함으로써 필요한 기능을 자동적으로 구현하는 기술이다. 이는 하드웨어 회로의 자동설계 가능성을 열어 주었지만, 아직 복잡한 회로를 얻기에는 한계가 있다. 본 논문에서는 진화 하드웨어의 적합도 공간을 분석하여, 다양한 개체가 동시에 진화되는 종분화 기법을 제안하고 그 효율성을 실험적으로 보인다. 또한 종분화 기법으로 얻은 다양한 회로를 분석하여 유용한 부가 기능이 창출될 수 있음을 보인다.

Keywords

References

  1. D. E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning, Addison Wesley, 1989
  2. X. Yao and T. Higuchi, 'Promises and challenges of evolvable hardware,' IEEE Trans. on Systems, Man, and Cybernetics, part C, vol. 29, pp. 87-97, February, 1999 https://doi.org/10.1109/5326.740672
  3. D. Albert, 'Evolutionary hardware overview,' http://citeseer.nj.nec.com/201089.html, 1997
  4. T. Higuchi, et al., 'Evolvable Hardware with Genetic Learning,' Proc. of IEEE Int. Symposium on Circuits and Systems, vol. 4, pp. 29-32, 1996 https://doi.org/10.1109/ISCAS.1996.541893
  5. M. Sipper, et al., 'A phylogenetic, ontogenetic, and epigenetic view of bio-inspired hardware systems,' IEEE Trans. on Evolutionary Computation, vol. 1, no. 1, pp. 83-97, 1997 https://doi.org/10.1109/4235.585894
  6. A Thompson, Hardware Evolution: Automatic Design of Elecronic Circuits in Reconfigurable Hardware by Artificial Evolution, London: Springer-Verlag, 1998
  7. T. Higuchi, et al., 'Evolvable hardware,' Massively Parallel Artificial Intelligence, pp. 398-421, MIT Press, 1994
  8. W. Liu, et al., 'ATM cell scheduling by function level evolvable hardware,' Proc. of the First Int. Conf. Evolvable Systems: From Biology to Hardware, pp. 180-192, Tsukuba, Japan, October, 1996
  9. T. Kalganova, 'An Extrinsic Function-Level Evolvable Hardware Approach,' Proc. of the Third European Conf. on Genetic Programming, Springer-Verlag, pp. 60-75, 2000
  10. J. Torresen, 'A divide-and-conquer approach to evolvable hardware,' Proc. of the 2nd Int. Conf. on Evolvable Systems: From Biology to Hardware, vol. 1478 of Lecture Notes in Computer Science, Springer-Verlag, pp. 57-65, Heidelberg, 1998
  11. V. K. Vassilev, 'Scalability Problems of Digital Circuit Evolution: Evolvability and Efficient Designs,' Proc. of the Second NASA/DoD Workshop on Evolvable Hardware, pp. 55-64, IEEE Computer Society, July, 2000 https://doi.org/10.1109/EH.2000.869342
  12. K. Deb and W. M. Spears, 'Speciation methods,' Evolutionary Computation 2: Advanced Algorithms and Operators, Institute of Physics Publishing, ch. 14, pp. 93-99, 2000
  13. R. I. McKay, 'Fitness sharing in genetic programming,' Genetic and Evolutionary Computation Conf., pp. 435-442, July, 2000
  14. 황금성, 조성배, '종분화를 이용한 다품종 하드웨어의 진화', 정보과학회 봄 학술발표 논문집(B), 제28권, 제1호, pp.307-309, 2001
  15. T. Back, 'Introduction to evolutionary algorithms,' Evolutionary Computation 1: Basic Algorithms and Operators, Institute of Physics Publishing, ch. 7, pp. 59-63, 2000
  16. S. W. Mahfoud, 'Niching Methods for Genetic Algorithms,' PhD thesis, University of Illinois at Urbana-Champaign, 1995
  17. P. Darwen and X. Yao, 'Every niching method has its niche: Fitness sharing and implicit sharing compared,' Proc. of Parallel Problem Solving from Nature (PPSN) IV, vol. 1141 of Lecture Notes in Computer Science, Springer-Verlag, pp. 398-407, 1996 https://doi.org/10.1007/3-540-61723-X_1004
  18. K. Deb and D. E. Goldberg, 'An investigation of niche and species formation in genetic function optimization,' Proc. 3rd Int. Conf. Genetic Algorithms, pp. 42-50, 1989
  19. J. E. Baker, 'Reducing bias and inefficiency in the selection algorithm,' In Proceedings of the Second Int. Conf. on Genetic Algorithms and their Application (J. J.Grefenstette ed.), pp. 14-21, 1987
  20. S. Trimberger, 'Reconfigurable Devices in the 21st Century,' Presentations of Invited Speakers on the Third NASA/DoD Workshop on Evolvable Hardware, July, 2001