Non-direct encoding method based on cellular automata to design neural network architectures

Computing and Informatics

Volumn 24, Issue 3, 2005, Pages 225-247

  Gutiérrez, German ^a,b,c   Sanchis, Araceli ^a,b,c   Isasi, Pedro ^a,d   Molina, José M ^a,b,c   Galván, Inés M ^a,b  

^a Scalab   (Spain)

^b UNIVERSIDAD CARLOS III DE MADRID   (Spain)

^c Complex Adaptive Systems Group ^*  (Spain)

^d Neural Network and Evolutionary Computation Laboratory

Author keywords

Cellular automata; Evolutionary neural network; Hyper heuristic approach for neural network architecture design; Indirect encoding

Indexed keywords

EID: 30844473077     PISSN: 13359150     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (36)

1. SIETSMA, J.-Dow, R. J.F.: Creating Artificial Neural Networks That Generalize. Neural Networks, Vol. 4, 1991, pp. 67-79.
2. MILLER, G.F.-TODD, P.M.-HEGDE, S.U.: Designing Neural Networks using Genetic Algorithms. In J. David Schaffer, editor, Proceedings of the Third International Conference on Genetic Algorithms, pages 379-384, San Mateo, California, 1989. Philips Laboratories, Morgan Kaufman Publishers, Inc.
3. HARP, S. A.-SAMAD, T.-GUHA, A.: Designing Application-Specific Neural Networks Using the Genetic Algorithm. In D. S. Touretzky, editor, Advances in Neural Information Processing Systems 2, pages 447-454. Morgan Kaufman, 1990.
4. GRUAU, F.: Genetic Synthesis of Boolean Neural Netorks with a Cell Rewriting Developmental Process. Proceedings of COGANN-92 International Workshop on Combinations of Genetic Algorithms and Neural Networks, pp. 55-74, IEEE Computer Society Press, 1992.
5. GRUAU, F.: Automatic Definition of Modular Neural Networks. Adaptive Behavior, Vol. 2, 1995, No. 3, pp. 151-183.
6. BILLINGS, S.A.-ZHENG, G.L.: Radial Basis Function Network Configuration Using Genetic Algorithms. Neural Networks, Vol. 8, 1995, No. 6, pp. 877-890.
7. YAO, X.-LIN, Y.: A New Evolutionary System for Evolving Artificial Neural Networks. Transactions on Neural Networks, Vol. 8, 1997, No. 3, pp. 694-713.
8. HUSSAIN, T. S.-BROWSE, R. A.: Attribute Grammars for Genetic Representations of Neural Networks and Syntactic Constraints of Genetic Programming. In AIVIGI '98: Workshop on Evolutionary Computation, 1998.
9. ROS, P.-SCHULENBURG, S.-MARÍN-BLAIQUEZ, J. G.-HART, E.: Hyper-Heuristics: Learning to Combine Simple Heuristicsin Bin-Packaging Problems. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2002), 2002.
10. Handbook of Metaheuristics Series: International Series in Operations Research and Management Science, Vol. 57, Glover, Fred W.; Kochenberger, Gary A. (Eds.) 2003, 570 p., Hardcover, ISBN: 1-4020-7263-5, Kluwer Academic Publishers.
11. MONTANA, D. J.-DAVIS, L. D.: Training Feedforward Networks Using Genetic Algorithms. In Proceedings of the International Joint Conference on Artificial Intelligence, San Mateo, CA, 1989. Morgan Kaufmann.
12. ALBA, E.-ALDANA, J. F.-TROYA, J. M.: Fully Automatic RNA Design: A Genetic Approach. X. Yao: Evolutionary Artificial Neural Networks 45. In Proc. of Int'l Workshop on Artificial Neural Networks (IWRNA '93), pages 399-404. Springer-Verlag, 1993. Lecture Notes in Computer Science, Vol. 686.
13. LEE, S.-W.: Off-Line Recognition of Totally Unconstrained Handwritten Numerals Using Multilayer Cluster Neural Network. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 18, 1996, pp. 648-652.
14. BELEW, R. K.-MCINERNEY, J.-SCHRAUDOLF, N.: Evolving Networks, Using the Genetic Algorithm with Connectionist Learning. Technical Report CSE-CS-174, UCSD, 1990.
15. MANDISCHER, M.: A Comparison of Evolution Strategies and Backpropagation for Neural Network Training. Neurocomputing, Vol. 42, 2002, pp. 87-117.
16. HWANG, M.W.-CHOI, J.Y.-PARK, J.: Evolutionary Projection Neural Networks. In Proceedings of the 1997 IEEE International Conference on Evolutionary Computation, ICEC'97, (Piscataway, NJ, USA), pp. 667-671, IEEE Press, 1997.
17. KIM, H.B.-JUNG, S. H.-KIM, T. G.-PARK, K. H.: Fast Learning Method for Backpropagation Neural Network by Evolutionary Adaptation of Learning Rates. Neurocomputing, Vol. 11, 1996, No. 1, pp. 101-106.
18. KROGH, A.-HERTZ, J.-PALMER, R. G.: Introduction to the Theory of Neural Computation. Addison-Wesley Publishing Company, Redwood City, CA, 1991.
19. YAO, X.: Evolving Artificial Neural Networks. Proceedings of the IEEE, Vol. 87, 1999, No. 9, p. 1423-1447.
20. GARIS, H.-FOGEL, D.-CONRAD, M.-YAO, X.: Special Issue on Evolutionary Neural Systems. Neurocomputing, Vol. 42, 2002, pp. 1-8.
21. ASH, T.: Dynamic Node Creation in Backpropagation Networks. ICS Report 8901, The Institute for Cognitive Science, University of California, San Diego (Saiensu-sh, 1988), 1988.
22. CAUDELL, T. P.-DOLAN, C.P.: Parametric Connectivity: Training of Constrained Networks using Genetic Algorithms. Proc. of the third International Conference on Genetic Algorithms and their Applications, pp. 370-374. Morgan Kaufman, 1989.
23. FOGEL, D. B.-FOGEL, L. J.-PORTO, V. W.: Evolving Neural Network, Biological Cybernetics, Vol. 63, 1990, pp. 487-493.
24. SCHAFFER, J. D.-CARUANA, R. A.-ESHELMAN, L.J.: Using Genetic Search to Exploit the Emergent Behaviour of Neural Networks. Physica D, Vol. 42, 1990, pp. 244-248.
25. KITANO, H.: Designing Neural Networks using Genetic Algorithms with Graph Generation System. Complex Systems. Vol. 4, 1990, pp. 461-476.
26. MOLINA, J.M.-TORRESANO, A.-GALVÁN, I. M.-ISASI, P.-SANCHIS, A.: Evolution of Context-Free Grammars for Designing Optimal Neural Networks Architectures. GECCO 2000, Workshop on Evolutionary Computation in the Development of ANN, USA, July 2000.
27. GUINEA, M. A.-GUTIERREZ, G.-GALVÁN, I.-SANCHIS, A.-MOLINA, J.M.: Generative Capacities of Grammars Codification for Evolution of NN Architectures. Congress on Evolutionary Computation, CEC 2002, IEEE World Congress on Computational Intelligence (IJCNN, FUZZ-IEEE, ICEC), Hawai, July 2002.
28. MJOLSNESS, E.-SHARP, D.H.-ALPERT, B.K.: Scaling Machine Learning and Genetic Neural Nets. Advances in applied mathematics, Vol. 10, 1989, pp. 137-163.
29. MERRIL, J.W.L.-PORT, R. F.: Fractally Configured Neural Networks. Neural Networks, Vol. 4, 1991, pp. 53-60.
30. VALLS, J.M.-GALVÁN, I.M.-MOLINA, J.M.: Multiagent System for Designing Optimal Radial Basis Neural Networks. Information Processing and Management of Uncertainty in Knowledge Based Systems, Spain, 2000.
31. WOLFRAM, S.: Theory and Applications of Cellular Automata. World Scientific, Singapore, 1988.
32. th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001, Granada, Spain, June 13-15, 2001, Proceedings, Part I, Editors: J. Mira, A. Prieto.
33. CYBENKO, G.: Approximation by Superposition of a Sigmoidal Function. Mathematics of Control, Signals and Systems, Vol. 2, 1989, pp. 303-314.
34. MINOR, J. M.: Parity with Two Layer Feedforward Nets. Neural Networks, Vol. 6, 1993, pp. 705-707.
35. SONTAG, E. D.: Feedforward Nets for Interpolation and Classification. Journal of Computer and System Sciences, Vol. 45, 1992.
36. BLAKE, C. L.-MERZ, C. J.: UCI Repository of Machine Learning Databases. 1998, available on http://www.ics.uci.edu/mlearn/MLRepository.html, Irvine, CA: University of California, Department of Information and Computer Science.