Towards memoryless model building

GECCO'08: Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation 2008

Volumn , Issue , 2008, Pages 2147-2152

  Iclǎnzan, David ^a   Dumitrescu, D ^a  

^a BABE BOLYAI UNIVERSITY   (Romania)

Author keywords

Adaptive neighborhood structure; Model based local search; Online model building

Indexed keywords

DECISION MAKING; LEARNING SYSTEMS; MODEL BUILDINGS; NEURAL NETWORKS; POPULATION STATISTICS;

ADAPTIVE NEIGHBORHOOD STRUCTURE; MACHINE LEARNING TECHNIQUES; MEMORY REQUIREMENTS; MODEL BASED LOCAL-SEARCH; ONLINE MODEL BUILDING; PROBABILISTIC MODELING; SMALL MEMORY REQUIREMENTS; STATISTICAL PROPERTIES;

BUILDINGS;

EID: 57349165452     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (18)

1. D. Dasgupta and Z. Michalewicz, editors. Evolutionary Algorithms in Engineering Applications. Springer-Verlag New York, Inc., Secaucus, NJ, USA, 2001.
2. E. D. de Jong, R. A. Watson, and D. Thierens. On the complexity of hierarchical problem solving. In H.-G. Beyer and U.-M. O'Reilly, editors, GECCO '05, pages 1201-1208. ACM, june 2005.
3. P. Grünwald, I. J. Myung, and M. Pitt. Advances in Minimum Description Length. MIT Press, Apr. 01 2005.
4. J. H. Holland. Adaptation in natural artificial systems. University of Michigan Press, Ann Arbor, 1975.
5. D. Iclanzan and D. Dumitrescu. Overcoming hierarchical difficulty by hill-climbing the building block structure. In D. T. et al, editor, GECCO '07: Proceedings of the 9th annual conference on Genetic and Evolutionary Computation, volume 2, pages 1256-1263, London, 7-11 July 2007. ACM Press.
6. D. Iclanzan and D. Dumitrescu. Going for the big fishes: Discovering and combining large neutral and massively multimodal building-blocks with model based macro-mutation. In GECCO '08: Proceedings of the 10th annual conference on Genetic and Evolutionary Computation. ACM Press, 12-16 July 2008. (accepted).
7. J. Jiang. Image compression with neural networks: A survey. SP:IC, 14(9):737-760, July 1999.
8. R. Johnston and H. Cartwright, editors. Applications of Evolutionary Computation in Chemistry. Springer, 2004.
9. T. Jones. Evolutionary Algorithms, Fitness Landscapes and Search. PhD thesis, University of New Mexico, Albuquerque, NM, 1995.
10. T. Kohonen. Self-organized formation of topologically correct feature maps. Biological Cybernetics, 43:59-69, 1982.
11. C. F. Lima, K. Sastry, D. E. Goldberg, and F. G. Lobo. Combining competent crossover and mutation operators: a probabilistic model building approach. In GECCO '05, pages 735-742, NY, USA, 2005. ACM.
12. M. Pelikan. Hierarchical Bayesian optimization algorithm: Toward a new generation of evolutionary algorithms. Springer Verlag, 2005.
13. M. Pelikan and D. E. Goldberg. Escaping hierarchical traps with competent genetic algorithms. In L. S. et al, editor, GECCO '01:, pages 511-518, San Francisco, California, USA, 7-11 2001. Morgan Kaufmann.
14. K. Sastry and D. E. Goldberg. Designing competent mutation operators via probabilistic model building of neighborhoods. In GECCO '04, pages 114-125. Springer, LNCS, vol. 3103, June 26-30, 2004.
15. R. A. Watson. Compositional Evolution: Interdisciplinary Investigations in Evolvability, Modularity, and Symbiosis. PhD thesis, Apr. 01 2002.
16. R. A. Watson, G. Hornby, and J. B. Pollack. Modeling building-block interdependency. In PPSN V: Proc. of the 5th International Conference on Parallel Problem Solving from Nature, pages 97-108, London, UK, 1998. Springer, LNCS.
17. R. A. Watson and J. B. Pollack. Hierarchically consistent test problems for genetic algorithms: Summary and additional results. In S. Brave, editor, GECCO '99: Late Breaking Papers, pages 292-297, Orlando, Florida, USA, 13 July 1999.
18. R. A. Watson and J. B. Pollack. Symbiotic composition and evolvability. In J. Kelemen and P. Sosik, editors, Advances in Artificial Life, 6th European Conf., (ECAL 2001), pages 480-490, Berlin, 2001. Springer.