메뉴 건너뛰기




Volumn 667 LNAI, Issue , 1993, Pages 442-459

An overview of evolutionary computation

Author keywords

[No Author keywords available]

Indexed keywords

CALCULATIONS; MACHINE LEARNING;

EID: 85028857450     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-56602-3_163     Document Type: Conference Paper
Times cited : (141)

References (47)
  • 1
    • 84889620692 scopus 로고
    • The philosophical errors that plague both evolutionary theory and simulated evolutionary programming
    • San Diego, CA: Evolutionary Programming Society
    • Atmar, W. (1992) The philosophical errors that plague both evolutionary theory and simulated evolutionary programming. Proceedings of the First Annual Conference on Evolutionary Programming, 27-34. San Diego, CA: Evolutionary Programming Society.
    • (1992) Proceedings of the First Annual Conference on Evolutionary Programming , pp. 27-34
    • Atmar, W.1
  • 3
    • 0002651837 scopus 로고
    • An overview of evolutionary algorithms for parameter optimization
    • Bäck, T., & Schwefel, H.-P. (1993) An overview of evolutionary algorithms for parameter optimization. Submitted to the Journal of Evolutionary Computation.
    • (1993) Journal of Evolutionary Computation
    • Bäck, T.1    Schwefel, H.-P.2
  • 6
    • 0002525028 scopus 로고
    • Evolutionary operation: A method of increasing industrial productivity
    • Box, G. E. P. (1957) Evolutionary operation: a method of increasing industrial productivity. Applied Statistics, Vol. 6, 81-101.
    • (1957) Applied Statistics , vol.6 , pp. 81-101
    • Box, G.E.P.1
  • 16
    • 0001044037 scopus 로고
    • Simulation of genetic systems by automatic digital computers
    • Fraser, A. S. (1957) Simulation of genetic systems by automatic digital computers. Australian Journal of Biological Science, 10, 484-491.
    • (1957) Australian Journal of Biological Science , vol.10 , pp. 484-491
    • Fraser, A.S.1
  • 17
    • 0002638043 scopus 로고
    • Using the genetic algorithm to generate LISP source code to solve the prisoner’s dilemma
    • Cambridge, MA: Lawrence Erlbaum
    • Fujiko, C., & Dickinson, J. (1987) Using the genetic algorithm to generate LISP source code to solve the prisoner’s dilemma. Proceedings of the Second International Conference on Genetic Algorithms, 236-240. Cambridge, MA: Lawrence Erlbaum.
    • (1987) Proceedings of the Second International Conference on Genetic Algorithms , pp. 236-240
    • Fujiko, C.1    Dickinson, J.2
  • 26
    • 0000746883 scopus 로고
    • Escaping brittleness: The possibilities of general-purpose learning algorithms applied to parallel rule-based systems
    • R. Michalski, J. Carbonell, T. Mitchell, Los Altos: Morgan Kaufmann
    • Holland, J. (1986) Escaping brittleness: The possibilities of general-purpose learning algorithms applied to parallel rule-based systems. In R. Michalski, J. Carbonell, T. Mitchell (eds.), Machine Learning: An Artificial Intelligence Approach. Los Altos: Morgan Kaufmann.
    • (1986) Machine Learning: An Artificial Intelligence Approach
    • Holland, J.1
  • 28
    • 0012694899 scopus 로고
    • Evolving a computer program to generate random numbers using the genetic programming paradigm
    • La Jolla, CA: Morgan Kaufmann
    • Koza, J. R. (1991) Evolving a computer program to generate random numbers using the genetic programming paradigm. Proceedings of the Fourth International Conference on Genetic Algorithms, 37-44. La Jolla, CA: Morgan Kaufmann.
    • (1991) Proceedings of the Fourth International Conference on Genetic Algorithms , pp. 37-44
    • Koza, J.R.1
  • 29
    • 0004158465 scopus 로고
    • Adaptation on rugged landscapes generated by iterated local interactions of neighboring genes
    • La Jolla, CA: Morgan Kaufmann
    • Lipsitch, M. (1991) Adaptation on rugged landscapes generated by iterated local interactions of neighboring genes. Proceedings of the Fourth International Conference on Genetic Algorithms, 128-135. La Jolla, CA: Morgan Kaufmann.
    • (1991) Proceedings of the Fourth International Conference on Genetic Algorithms , pp. 128-135
    • Lipsitch, M.1
  • 36
    • 0001961776 scopus 로고
    • Dynamic parameter encoding for genetic algorithms
    • Schraudolph, N. N., & Belew, R. K. (1992) Dynamic parameter encoding for genetic algorithms. Machine Learning Journal, Volume 9, Number 1, 9-22.
    • (1992) Machine Learning Journal , vol.9 , Issue.1 , pp. 9-22
    • Schraudolph, N.N.1    Belew, R.K.2
  • 38
  • 42
    • 4344688585 scopus 로고
    • Naval Research Laboratory AI Center Report AIC-92-025. Washington, DC 20375 USA
    • Spears, W. M. (1992b) Adapting crossover in a genetic algorithm. Naval Research Laboratory AI Center Report AIC-92-025. Washington, DC 20375 USA.
    • (1992) Adapting Crossover in a Genetic Algorithm
    • Spears, W.M.1
  • 44
    • 0003389370 scopus 로고
    • The GENITOR algorithm and selection pressure: Why rank-based allocation of reproductive trials is best
    • Fairfax, VA: Morgan Kaufmann
    • Whitley, D. (1989) The GENITOR algorithm and selection pressure: why rank-based allocation of reproductive trials is best. Proceedings of the Third International Conference on Genetic Algorithms, 116-121. Fairfax, VA: Morgan Kaufmann.
    • (1989) Proceedings of the Third International Conference on Genetic Algorithms , pp. 116-121
    • Whitley, D.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.