jsims@mwunix.mitre.org (James Sims) (01/23/91)
Can someone point me to a (hopefully) existing comparision between various learning techniques - GA, Neural Nets, Adaptive Control Theory, learning in rulebases, etc in the literature? If not, are there survey references that describe the strengths/weaknesses of each of these approaches individually? reply by email to sims@starbase.mitre.org, I'll summarize to the net. thanks in advance, jim
tgd@tesla.orst.EDU (Tom Dietterich) (01/25/91)
Many people have been comparing alternative learning algorithms.
In IJCAI-89 (International Joint Conference on Artificial Intelligence),
there were three papers published:
Weiss, S., and Kapouless, I., (1989). An empirical comparison
of pattern recognition, neural nets, and machine learning
classification methods. {\it IJCAI-89: Eleventh International Joint
Conference on Artificial Intelligence}. 781--787.
Mooney, R., Shavlik, J., Towell, G., and Gove, A. (1989). An
experimental comparison of symbolic and connectionist learning
algorithms. {\it IJCAI-89: Eleventh International Joint Conference on
Artificial Intelligence}. 775--80.
Fisher, D. H., and McKusick, K. B., (1988). An empirical
comparison of ID3 and back-propagation. {\it IJCAI-89: Eleventh
International Joint Conference on Artificial Intelligence}. 788--793.
At the last three meetings of NIPS (Neural Information Processing Systems),
there have been talks comparing a wide range of methods.
Gish, S. L. and Blanz, W. E. 1990. Comparing the performance of connectionist
and statistical classifiers on an image segmentation problem. In D. Touretzky
(Ed.), Advances in Neural Information Processing Systems (Vol. 2).
San Mateo, CA: Morgan Kauffman. 614--621.
Atlas, L., Cole, R., Connor, J., El-Sharkawi, M., Marks, R. J. II,
Muthusamy, Y., Barnard, E. 1990. Performance comparisons between
backpropagation
networks and classification trees on three real-world applications.
In D. Touretzky (Ed.), Advances in Neural Information Processing Systems
(Vol. 2). San Mateo, CA: Morgan Kauffman. 622-629.
Tsoi, A. C., and Pearson, R. A. 1991. Comparison of three classification
techniques: CART, C4.5, and multi-layer perceptrons. To appear in
D. Touretzky (Ed.), Advances in neural Information Processing Systems
(Vol 3.), San Mateo, CA: Morgan Kaufmann.
Ng, K. and Lippmann, R. P. 1991. A comparative study of the practical
characteristics of neural network and conventional pattern classifiers.
To appear in D. Touretzky (Ed.), Advances in neural Information
Processing Systems (Vol 3.), San Mateo, CA: Morgan Kaufmann.
Finally, my students and I have contributed to this literature as well:
Dietterich, T. G., Hild, H., Bakiri, G. (1990) A comparative
study of ID3 and backpropagation for English text-to-speech mapping.
{\it Proceedings of the Seventh International Conference on Machine
Learning} (pp. 24--31). Austin, TX: Morgan Kaufmann.
I'm sure I've missed some papers. These are just the ones that I could
find in a few minutes.
Thomas G. Dietterich
Department of Computer Science
Dearborn Hall, 303
Oregon State University
Corvallis, OR 97331-3102
503-737-5559