Review of "Genetic Algorithms for Machine Learning by John J. Greffenstette", Kluwer Academic Publishers, 1993.

ABSTRACT

This book is a reprint from a special issue of the journal Machine Learning on Genetic Algorithms (GAs). The fact that it was the third special issue of the journal on GAs shows the continuous increase of interest of people in the field. The five selected articles were presented at the Fourth International Conference on Genetic Algorithms, in June 1991 (San Diego), and at a Special Workshop for Machine Learning at the same conference. The intended book audience is both researchers and practitioners in the field.

REFERENCES

• 1: Dimitri P. Bertsekas , John N. Tsitsiklis, Neuro-Dynamic Programming, Athena Scientific, 1996
• 2: Dracopoulos, D. C. and Jones., A. J. "Neuro-genetic adaptive attitude control." In Neural Computing & Applications, 2(4):183--204, 1994.
• 3: David E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley Longman Publishing Co., Inc., Boston, MA, 1989
• 4: Kaufman, K. A, Michalski, R. S. and Schutz, A. C. "Emerald 1: An integrated system of machine learning and discovery programs for education and research." Technical Report MLI-89-12, George Mason University, 1989.
• 5: Koza, J. R. Genetic Programming. MIT Press, 1982.
• 6: Koza, J. R. Genetic Programming II. MIT Press, 1994.
• 7: Zbigniew Michalewicz, Genetic algorithms + data structures = evolution programs (3rd ed.), Springer-Verlag, London, 1996
• 8: Melanie Mitchell, An introduction to genetic algorithms, MIT Press, Cambridge, MA, 1996
• 9: Richard S. Sutton, Learning to Predict by the Methods of Temporal Differences, Machine Learning, v.3 n.1, p.9-44, August 1988 [doi>10.1023/A:1022633531479]
• 10: Reiko Tanese, Distributed genetic algorithms, Proceedings of the third international conference on Genetic algorithms, p.434-439, December 1989, George Mason University, United States
• 11: Werbos, P. J. "Neurocontrol and supervised learning." In White, D. A. and Sofge, D. A. (Eds.), Handbook of Intelligent Control, chapter 3. Van Nostrand Reinhold, 1992.
• 12: Werbos, P. J. Learning in the brain: An engineering interpretation. In Pribram, K. (Ed.), Learning as Self-Organization. Erlbaum, 1996.
• 13: J. Wnek , J. Sarma , A. A. Wahab , R. S. Michalski, Comparing learning paradigms via diagrammatic visualization: a case study in single concept learning using symbolic, neural net and genetic algorithm methods, Methodologies for intelligent systems, 5, Elsevier North-Holland, Inc., New York, NY, 1991