A population-based incremental learning algorithm with elitist strategy

Proceedings - Third International Conference on Natural Computation, ICNC 2007

Volumn 3, Issue , 2007, Pages 583-587

  Qingbin, Zhang ^a   Tihua, Wu ^a   Bo, Liu ^a  

^a YANSHAN UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATION THEORY; CONVERGENCE OF NUMERICAL METHODS; GENETIC ALGORITHMS; POPULATION STATISTICS; PROBLEM SOLVING;

CONVERGENCE SPEED; POPULATION-BASED INCREMENTAL LEARNING (PBIL); SOLUTION QUALITY;

LEARNING ALGORITHMS;

EID: 38049061657     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICNC.2007.126     Document Type: Conference Paper

References (9)

1. Larrañaga P, Lozano J A., Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation, Kluwer Academic Publishers, 2002.
2. S. Baluja, "Population-Based Incremental Learning: A Method for Integrating Genetic Search Based Function Optimization and Competitive Learning", Carnegie Mellon University, Technical Report CMU-CS-94-163, 1994.
3. Baluja. S, Caraana. R, "Removing the genetics from the standard genetic algorithm", Carnegie Mellon University, Technical Report CMU-CS-95-141, 1995.
4. Baluja. S, "Genetic Algorithms and Explicit Search Statistics", In Mozer, M.C., Jordan, M.I., Petsche, T. (Eds.), Advances in Neural Information, Processing Systems 9, MIT Press, Cambridge, MA, 1997, pp319-325.
5. Elvis Galic, Markus Höhfeld, "Improving the Generalization Performance of Multi-Layer-Perceptrons with Population-Based Incremental Learning", Proceedings of the 4th International Conference on Parallel Problem Solving from Nature, Lecture Notes in Computer Science, Vol. 1141, Springer-Verlag, 1996, pp740 - 750.
6. Andrei Petrovski, Siddhartha Shakya, John McCall, "Optimising cancer chemotherapy using an estimation of distribution algorithm and genetic algorithms", Proceedings of the 8th annual conference on Genetic and evolutionary computation, Seattle, Washington, USA, ACM Press, 2006, pp413-418.
7. B Yuan, M Gallagher, "Playing in Continuous Spaces: Some Analysis and Extension of Population-Based Incremental Learning", Proceedings of Congress of Evolutionary Computation (CEC), 2003, pp443- 450.
8. JL Shapiro, "The Sensitivity of PBIL to the Learning Rate, and How Detailed Balance Can Remove It", In Carlos Cotta, Kenneth de Jong, Riccardo Poli, and Jonathan Rowe, editors, Foundations of Genetic Algorithms VII, Morgan Kaufmann, 2002.
9. J Očenášek, Parallel Estimation of Distribution Algorithms, Brno University of Technology, Faculty of Information Technology, Doctoral Thesis, 2002.