Learning in stages: A layered learning approach for genetic programming

2012 IEEE RIVF International Conference on Computing and Communication Technologies, Research, Innovation, and Vision for the Future, RIVF 2012

Volumn , Issue , 2012, Pages

  Hien, Nguyen Thi ^a   Hoai, Nguyen Xuan ^b  

^a LE QUY DON TECHNICAL UNIVERSITY   (Viet Nam)

^b HANOI UNIVERSITY   (Viet Nam)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL COSTS; GENERALISATION; LAYERED LEARNING; PROGRESSIVE SAMPLING; REAL-WORLD PROBLEM; SUBSTANTIAL REDUCTION;

GENETIC PROGRAMMING; INNOVATION;

LEARNING SYSTEMS;

EID: 84860491263     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/rivf.2012.6169838     Document Type: Conference Paper

References (14)

1. U. Bhowan, M. Johnston, and Silva, "Evolving ensembles in multiobjective genetic programming for classification with unbalanced data," in GECCO '11: Proceedings of the 13th annual conference on Genetic and evolutionary computation. Dublin, Ireland: ACM, 12-16 jul 2011, pp. 1331-1338.
2. C. Blake, E. Keogh, and C. J. Merz, "Uci repository of machine learning databases," Department of Information and Computer Science, University of California, Irvine, CA, 1998. [Online]. Available: http://www.ics.uci.edu/ mlearn/MLRepository.html
3. B. Gu, B. Liu, F. Hu, and H. Liu, "Efficiently determine the starting sample size for progressive sampling," in DMKD, 2001.
4. S. M. Gustafson, "Layered learning in genetic programming for a co-operative robot soccer problem," Master's thesis, Kansas State University, Manhattan, KS, USA, dec 2000. [Online]. Available: http://www.cs.nott.ac.uk/ smg/research/publications/msthesis-2000.ps
5. D. Jackson and A. P. Gibbons, "Layered learning in boolean gp problems," in Proceedings of the 10th European Conference on Genetic Programming, ser. Lecture Notes in Computer Science, M. Ebner, M. O'Neill, A. Ekárt, L. Vanneschi, and A. I. Esparcia-Alcázar, Eds., vol. 4445. Valencia, Spain: Springer, 11-13 apr 2007, pp. 148-159.
6. J. R. Koza, Genetic Programming: On the Programming of Computers by Means of Natural Selection. Cambridge, MA, USA: MIT Press, 1992.
7. T. Mitchell, Machine Learning. McGraw-Hill, 1997.
8. T. H. Nguyen, X. H. Nguyen, and R. I. McKay, "A study on genetic programming with layered learning and incremental sampling," in Proceedings of the 2011 IEEE Congress on Evolutionary Computation, A. E. Smith, Ed., IEEE Computational Intelligence Society. New Orleans, USA: IEEE Press, 5-8 jun 2011, pp. 1184-1190.
9. R. Poli, W. B. Langdon, and N. F. McPhee, A field guide to genetic programming. Published via http://lulu.com and freely available at http://www.gp-field-guide.org.uk, 2008. [Online]. Available: http://www.gp-field-guide.org.uk
10. F. J. Provost, D. Jensen, and T. Oates, "Efficient progressive sampling," in KDD, 1999, pp. 23-32.
11. P. Stone, "Layered learning in multi-agent systems," Ph.D. dissertation, School of Computer Science, Carnegie Mellon University, dec 1998. [Online]. Available: http://www.cs.cmu.edu/ pstone/thesis/
12. P. Stone and M. M. Veloso, "Layered learning," in Machine Learning: ECML 2000, 11th European Conference on Machine Learning, Barcelona, Catalonia, Spain, May 31 - June 2, 2000, Proceedings, ser. Lecture Notes in Artificial Intelligence, vol. 1810. Springer, 2000, pp. 369-381.
13. L. Vanneschi, M. Castelli, and S. Silva, "Measuring bloat, overfitting and functional complexity in genetic programming," in GECCO '10: Proceedings of the 12th annual conference on Genetic and evolutionary computation. Portland, Oregon, USA: ACM, 7-11 jul 2010, pp. 877-884.
14. P. Vlachos, "Statlib project repository," Department of Statistics, Carnegie Mellon University, Pittsburgh, PA, 2000. [Online]. Available: http://lib.stat.cmu.edu