Accelerating the evolutionary-gradient-search procedure: Individual step sizes

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1498 LNCS, Issue , 1998, Pages 408-417

  Salomon, Ralf ^a  

^a UNIVERSITY OF ZURICH   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER SCIENCE; COMPUTERS;

EVOLUTION STRATEGIES; EVOLUTIONARY GRADIENTS; FASTER CONVERGENCE; GRADIENT DIRECTION; RECENT RESEARCHES; STEP SIZE; TEST FUNCTIONS;

STEEPEST DESCENT METHOD;

EID: 84878614290     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/bfb0056883     Document Type: Conference Paper

References (18)

1. Bäck, T., Schwefel, H.-P.: An Overview of Evolutionary Algorithms for Parameter Optimization. Evolutionary Computation 1(1) (1993) 1-23
2. Bäck, T., Kursawe, F.: Evolutionary Algorithms for Fuzzy Logic: A Brief Overview. In: Bouchon-Meunier, B., Yager, R.R., Zadeh, L.A. (eds.): Fuzzy Logic and Soft Computing, Vol. IV. World Scientific, Singapore (1995) 3-10
3. Beyer, H.-G.: An Alternative Explanation for the Manner in which Genetic Algorithms Operate. BioSystems 41 (1997) 1-15
4. Fogel, D.B.: Evolutionary Computation: Toward a New Philosophy of Machine Learning Intelligence. IEEE Press, Jersy, NJ (1995)
5. Fogel, L.J.: "Autonomous Automata". Industrial Research 4 (1962) 14-19
6. Goldberg, D.E.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Publishing Company (1989)
7. Hansen, N., Ostermeier, A.: Adapting Arbitrary Normal Mutation Distributions in Evolution Strategies: The Covariance Matrix Adaptation. In: Proceedings of The 1996 IEEE International Conference on Evolutionary Computation (IECEC96). IEEE (1996) 312-317
8. Hansen, N., Ostermeier, A.: Convergence Properties of Evolution Strategies with the Derandomized Covariance Matrix Adaptation: The (μ/μI, λ)-CMA-ES. In: Zimmermann, H.-J. (ed.): Proceedings of The Fifth Congress on Intelligent Techniques and Soft Computing EUFIT'97. Verlag Mainz, Achen, (1997) 650-654
9. Luenberger, D.G.: Linear and Nonlinear Programming. Addison-Wesley, Menlo Park, CA (1984)
10. Mühlenbein, H., Schlierkamp-Voosen, D.: Predictive Models for the Breeder Genetic Algorithm I. Evolutionary Computation 1(1) (1993) 25-50.
11. Press, W.H., Teukolsky, S.A., Vetterling, W.T., Flannery, B.P.: Numerical Recipes in C. Cambridge University Press, Cambridge, UK (1994)
12. Rechenberg, I.: Evolutionsstrategie. Frommann-Holzboog, Stuttgart (1994)
13. Rumelhart et al. (eds.): Parallel Distributed Processing: Explorations in the Microstructure of Cognition, Vol. 2. The MIT Press, Cambridge, MA (1986)
14. Salomon, R.: Reevaluating Genetic Algorithm Performance under Coordinate Rotation of Benchmark Functions; A survey of some theoretical and practical aspects of genetic algorithms. BioSystems 39(3) (1996) 263-278
15. Salomon, R.: The Evolutionary-Gradient-Search Procedure. In: Koza, J. et al. (eds.): Genetic Programming 1998: Proceedings of the Third Annual Conference, July 22-25, 1998. Morgan Kaufmann, San Francisco, CA (1998)
16. Salomon, R., van Hemmen, J.L.: Accelerating backpropagation through dynamic self-adaptation. Neural Networks 9(4) (1996) 589-601
17. Schwefel, H.-P.: Evolution and Optimum Seeking. John Wiley and Sons, NY (1995)
18. Schwefel, H.-P.: Evolutionary Computation - A Study on Collective Learning. In: Callaos, N., Khoong, CM., Cohen, E. (eds.): Proceedings of the World Multicon-ference on Systemics, Cybernetics and Informatics, vol. 2. Int'l Inst. of Informatics and Systemics, Orlando FL (1997) 198-205