Applicability of estimation of distribution algorithms to the fuzzy rule learning problem: A preliminary study

ICEIS 2002 - Proceedings of the 4th International Conference on Enterprise Information Systems

Volumn 1, Issue , 2002, Pages 350-357

  Flores, M Julia ^a   Gamez, Jose A ^a  

^a UNIVERSITY OF CASTILLA LA MANCHA   (Spain)

Author keywords

Estimation of distribution algorithms; Evolutionary computation; Expert systems; Fuzzy rule based systems; Machine learning

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMBINATORIAL OPTIMIZATION; EXPERT SYSTEMS; FUZZY RULES; GENETIC ALGORITHMS; INFORMATION SYSTEMS; LEARNING ALGORITHMS; LEARNING SYSTEMS;

ESTIMATION OF DISTRIBUTION ALGORITHMS; FUZZY LINGUISTICS; FUZZY RULE LEARNING; FUZZY RULE-BASED SYSTEMS; INPUT PARAMETER; REAL-WORLD PROBLEM; UNIVARIATE MODELS;

EVOLUTIONARY ALGORITHMS;

EID: 33845275153     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (23)

1. Baluja, S. (1994). Population-Based Incremental Learning: A Method for Integrating Genetic Search Based Function Optimization and Competitive Learning, TR CMU-CS-94-163, Computer Science, Carnegie Mellon University.
2. Baluja, S. and Davies, S. (1997). Combining multiple optimization runs with optimal dependecy trees, TR CMU-CS-97-157, Computer Science, Carnegie Mellon University.
3. Bardossy, A. and Duckstein, B. (1995). Fuzzy rule-based modeling with application to geophysical, biological and engineering systems, CRC Press.
4. Blanco, R. and Inza, I. and Larranaga, P. (2001). Learning Bayesian networks from data by novel populationbased, stochastic search algorithms, Actas de la IX Conferencia de la Asociacion Española para la Inteligencia Artificial.
5. Casillas J. and Cordon, O. and Herrera, F. (2000). Improving the Wang and Mendel's Fuzzy Rule Learning Method by Inducing Cooperation Among Rules, 8th Int. Conf. on Information Processing and Management of Uncertainty in Knowledge-Based Systems.
6. Casillas, J. and Cordon, O. and Herrera, F. (2000b). Learning Cooperative Fuzzy Linguistic Rules Using Ant Colony Optimization Algorithms, TR DECSAI-00119, University of Granada.
7. Chow, C. and Liu, C. (1968). Approximating discrete probability distributions with dependence trees, IEEE Trans. on Information Theory, Vol. 14, Pages 462-467.
8. De Bonet, J. S. and Isbell, C. L. and Viola, P. (1997). MIMIC: Finding optima by estimating probability densities, En Advances in Neural Information Processing Systems, Vol. 9.
9. Hirota, K. (1993). Industrial applications of fuzzy technology, Springer-Verlag.
10. Larranaga, P. and Etxeberria, R. and Lozano, J. A. and Pena, J. M. (2000). Combinatorial optimization by learning and simulation of Bayesian networks, Proc. of the 16th Conference on Uncertainty in Artificial Intelligence. Pages 343-352.
11. Larranaga P. and Lozano, J. A. (2001). Estimation of Distribution Algorithms. A New Tool for Evolutionary Computation, Kluwer Academic Press.
12. Michalewicz, Z. (1996). Genectic Algorithms + Data Structures = Evolution Programs. Springer-Verlag.
13. Mitchell, T. M. (1997) Machine Learning, McGraw-Hill.
14. Muhlenbein, H. (1998). The equation for response to selection and its use for prediction, Evolutionary Computation.
15. Nozaki, K. and Ishibuchi, H. and Tanaka, H. (1997). A symple but powerful heuristic method for generating fuzzy rules from numerical data, Fuzzy Sets and Systems, 86:251-270.
16. Orchard, R. A. (1995). FuzzyClips Version 6.04: User Guide, Knowledge Systems Laboratory, Institute for Information Technology, National Research Council Canada.
17. Sugeno, M. and Kang, G. T. (1988). Structure identification of fuzzy models, Fuzzy Sets and Systems, 28:15-33.
18. Takagi, T. and Sugeno, M. (1985). Fuzzy identification of systems and its application to modeling and control, IEEE Transactions on Systems, Man and Cybernetics, 15:116-132.
19. Wang, L. X. and Mendel, J. M. (1992). Generating fuzzy rules by learning from examples, IEEE Transactions on Systems, Man, and Cybernetics.
20. Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8:338-353.
21. Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning, Part I: Information Science 8:199-249
22. Part II: Information Science 8:301-357
23. Part III: Information Science 9:43-80.