CONTINUOUS EVOLUTIONARY PROGRAMMING - ANALYSIS AND EXPERIMENTS

被引：23

作者：

FOGEL, GB ^{[1
]}

FOGEL, DB ^{[1
]}

机构：

[1] UNIV CALIF LOS ANGELES,DEPT BIOL,LOS ANGELES,CA 90024

来源：

CYBERNETICS AND SYSTEMS | 1995年 / 26卷 / 01期

关键词：

D O I：

10.1080/01969729508927488

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Evolutionary programming is a method for simulating evolution that emphasizes the behavioral rather than the genetic relationship of parents and their offspring. In a typical evolutionary program, every parent simultaneously generates a number of offspring, which are all subsequently placed in competition. Evolution can be abstracted as a more continuous process by generating only a single offspring from one parent and then immediately placing it in competition with all existing solutions. Some theoretical observations are made with respect to this new model. The results of empirical trials on a test landscape with multiple local minima indicate that the standard method of reproduction and selection may be more appropriate for practical optimization problems.

引用

页码：79 / 90

页数：12

共 30 条

[1]

Atmar J.W., Speculation of the evolution of intelligence and its possible realization in machine form, Doctoral Dissertation, (1976)

[2]

Back T., Schwefel H.-P., An overview of evolutionary algorithms for parameter optimization, Evolutionary Comput, 1, 1, pp. l-24, (1993)

[3]

Barricelli N.A., Symbiogenetic evolution processes realized by artificial methods, Methodos, 9, 35-36, pp. 143-182, (1957)

[4]

Bohachevsky I.O., Johnson M.E., Stein M.L., Generalized simulated annealing for function optimization, Technometrics, 28, 3, pp. 209-218, (1986)

[5]

Bremermann H.J., Optimization through evolution and recombination, In Self-Organizing Systems, pp. 93-106, (1962)

[6]

Burgin G.H., On playing two-person zero-sum games against nonminimax players, IEEE Trans. Syst. Sci. Cybernet, SSC-5, 4, pp. 369-370, (1969)

[7]

Fogel D.B., System Identification through Simulated Evolution: A Machine Learning Approach to Modeling.Needham, MA: Ginn, (1991)

[8]

Fogel D.B., Evolving artificial intelligence, Doctoral Dissertation, (1992)

[9]

Fogel D.B., Asymptotic convergence of genetic algorithms and evolutionary programming: Analysis and experiments, Cybernet. Syst, 25, pp. 389-407, (1994)

[10]

Fogel D.B., Evolutionary Computation: Toward a New Philosophy of Biology, (1995)

← 1 2 3 →