The evolutionary-gradient-search procedure in theory and practice

Studies in Computational Intelligence

Volumn 193, Issue , 2009, Pages 77-101

  Salomon, Ralf ^a   Arnold, Dirk V ^b  

^a UNIVERSITY OF ROSTOCK   (Germany)

^b DALHOUSIE UNIVERSITY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 65749112358     PISSN: 1860949X     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-00267-0_3     Document Type: Article

References (22)

1. Arnold, D.: An analysis of evolutionary gradient search. In: Proceedings of the Congress on Evolutionary Computation (CEC 2004), pp. 47-54. IEEE Press, Los Alamitos (2004)
2. Arnold, D., Salomon, R.: Evolutionary gradient search revisited. Techreport CS-2005-09, Faculty of Computer Science, Dalhousie University (2005)
3. Arnold, D., Beyer, H.G.: Local performance of the (μ/μ,λ -Evolution Strategy in a noisy environment. In: Martin, W.N., Spears, W.M. (eds.) Proceeding of Foundation of Genetic Algorithms 6 (FOGA 2006), pp. 127-141. Morgan Kaufmann, San Francisco (2001)
4. Arnold, D., Salomon, R.: Evolutionary gradient search revisited. IEEE Transactions on Evolutionary Computation 11(4), 480-495 (2007)
5. Bäck, T., Schwefel, H.P.: An overview of evolutionary algorithms for parameter optimization. Evolutionary Computation 1(1), 1-23 (1993)
6. Beyer, H.G.: An alternative explanation for the manner in which genetic algorithms operate. BioSystems 41, 1-15 (1997)
7. Beyer, H.G.: The Theory of Evolution Strategies. Springer, Heidelberg (2001)
8. Fogel, D.B.: Evolutionary Computation: Toward a New Philosophy of Machine Learning Intelligence. IEEE Press, Piscataway (1995)
9. Fogel, L.J.: Autonomous automata. Industrial Research 4, 14-19 (1962)
10. Goldberg, D.E.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, Reading (1989)
11. Hansen, N., Ostermeier, A.: Completely derandomized self-adaptation in evolution strategies. Evolutionary Computation 9(2), 159-195 (2001)
12. Luenberger, D.G.: Linear and Nonlinear Programming. Addison-Wesley, Reading (1984)
13. Ostermeier, A., Gawelczyk, A., Hansen, N.: Step-size adaptation based on non-local use of selection information. In: Davidor, Y., änner, R.M., Schwefel, H.P. (eds.) Proceedings of the 3rd International Conference on Parallel Problem Solving from Nature (PPSN III), pp. 189-198. Springer, Heidelberg (1994)
14. Press, W.H., Teukolsky, S.A., Vetterling, W.T., Flannery, B.P.: Numerical Recipes in C. Cambridge University Press, Cambridge (1994)
15. Rechenberg, I.: Evolutionsstrategie 1994. Frommann-Holzboog, Stuttgart (1994)
16. Rudolph, G.: On correlated mutations in evolution strategies. In: änner, R.M., Manderick, B. (eds.) Proceedings of the 2nd International Conference on Parallel Problem Solving from Nature (PPSN II), pp. 105-114. Elsevier, Amsterdam (1992)
17. Rumelhart, et al. (eds.): Parallel Distributed Processing: Explorations in the Microstructure of Cognition, vol. 2. MIT Press, Cambridge (1986)
18. Salomon, R.: Evolutionary algorithms anS gradient search: similarities and differences. IEEE Transactions on Evolutionary Computation 2(2), 45-55 (1998)
19. Salomon, R.: Accelerating the Evolutionary-Gradient-Search procedure: Individual step sizes. In: Eiben, A.E., Bäck, T., Schoenauer, M., Schwefel, H.P. (eds.) Proceedings of the 5th International Conference on Parallel Problem Solving from Nature (PPSN V), pp. 408-417. Springer, Heidelberg (1998)
20. Salomon, R., van Hemmen, J.L.: Accelerating backpropagation through dynamic self-adaptation. Neural Networks 9(4), 589-601 (1996)
21. Schwefel, H.P.: Evolution and Optimum Seeking. John Wiley and Sons, Chichester (1995)
22. Schwefel, H.P.: Evolutionary Computation - A Study on Collective Learning. In: Callaos, N., Khoong, C.M., Cohen, E. (eds.) Proceedings of the World Multiconference on Systemics, Cybernetics and Informatics, Orlando, FL, USA. International Institute of Informatics and Systemics, vol. 2, pp. 198-205 (1997)