A note on the population based incremental learning with infinite population size

2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005. Proceedings

Volumn 1, Issue , 2005, Pages 198-205

  Rastegar, R ^a   Meybodi, M R ^a  

^a AMIRKABIR UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

[No Author keywords available]

Indexed keywords

ASYMPTOTIC STABILITY; FUNCTIONS; OPTIMIZATION;

BOLTZMANN SELECTION SCHEMAS; POPULATION BASED INCREMENTAL LEARNING (PBIL);

LEARNING ALGORITHMS;

EID: 27144497783     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (20)

1. Baluja, S., "Population Based Incremental Learning: A Method for Integrating Genetic Search Based Function Optimization and Competitive Learning", Technical Report, Carnegie Mellon University, 1994.
2. Baluja, S., and Davis, S., "Fast Probabilistic Modeling for Combinatorial Optimization", Proceedings of the 15 National Conference on Artificial Intelligence, Madison, Wisconsin, AAAI Press, pp. 469-476, 1998.
3. Bonet, D., Isbell, J. S., and Viola, P., "MIMIC: Finding Optima by Estimation Probability Densities", Advances in Neural Information Processing Systems, Vol. 9, pp. 424-431, Cambridge, MIT Press, 1997.
4. González, C., Lozano, J. A., and Larrañaga, P., "Analyzing the PBIL Algorithm by Means of Discrete Dynamical Systems, Complex Systems, Vol. 12, pp. 465-479, 2000.
5. th International Conference on Artificial Neural Networks and Genetic Algorithms, ICANNGA'2001.
6. Harik, G. R., Lobo, F., G., and Goldberg, D. E., "The Compact Genetic Algorithm", IEEE Transaction on Evolutionary Computation, Vol. 3, No. 4, 1999.
7. th IEEE Conferences on Evolutionary Computation, Indianapolis, IEEE Press, pp. 1-5, 1997.
8. Larrañaga, P., and Lozano, J. A., Estimation of Distribution Algorithms. A New tools for Evolutionary Computation, Kluwer Academic Publishers, 2001.
9. Maxwell, B., and Anderson, S., "Training Hidden Markov Models using Population-Based Incremental Learning", In Genetic and Evolutionary Computation Conference, GECCO-99, 1999.
10. Mühlenbein, H., "The Equation for Response to Selection and Its Use for Prediction", Evolutionary Computation, Vol. 5, pp. 303-346, 1998.
11. Mühlenbein, H., and Mahnig, T., "Convergence Theory and Application of the Factorized Distribution Algorithm", Journal of Computing and Information Technology, Vol 7, PP. 19-32, 1999.
12. Mühlenbein, H., Mahnig, T., and Rodriguez, A. O., "Schemata, Distributions and Graphical Models in Evolutionary Optimization", Journal of Heuristics, Vol. 5, pp. 215-247, 1999.
13. Pelikan, M., Goldberg D. E., and Cantz Paz, E., "BOA: the Bayesian Optimization Algorithm", Proceedings of the Genetic and Evolutionary Computation Conference, Orlando, Morgan Kaufmann Publishers, pp. 525-532, 1999.
14. Rastegar, R., and M. R. Meybodi, "A New Estimation of Distribution Algorithm based on Learning Automata", to appear in the proceedings of IEEE Conference on Evolutionary Computation 2005, UK, 2005.
15. Sebag, M., and Ducoulombier, A., "Extending Population-Based Incremental Learning to Continues Search Spaces", in Parallel Problem Solving from Nature, SN-V, pp. 418-427, Springer, 1998.
16. Servais, M. P., De Jaer, G., and Greene, J. R., 22Function Optimization using Multiple-Base Population Based Incremental Learning", In Proceedings of the Eighth South African Workshop on Pattern Recognition, 1997.
17. Sheinerman, E. R., Invitation to Dynamical Systems, Printice-Hall, 1996.
18. Vose, M. D., "Random Heuristic Search", Theoretical Computer Science, No. 229, Vol. 1-2, pp. 103-142, 1999.
19. Zhang, Q., "On Stability of Fixed Points of Limit Models of Univariate Marginal Distribution Algorithm and Factorized Distribution Algorithm", IEEE Transactions on Evolutionary Computation, Vol. 8, No. 1, 2004.
20. Zhang, Q., and Mühlenbein, H., "On the Convergence of a Class of Estimation of Distribution Algorithms", IEEE Transaction on Evolutionary Computation, Vol. 8, No. 2, 2004.