Abstract
Simple implementation of genetic programming by making use of the column tables is discussed. Implementations of Koza’s genetic programming in compiled languages are usually not most efficient when crossover is applied. If chromosomes are directed acyclic graphs, more efficient than rooted trees both in memory requirement as well as in evaluation time of chromosome, then crossover requires traversing the data structures and their preliminary analysis. Column tables inherently code directed acyclic graphs, the implementation of crossover is simple and needs neither traversing nor checking of integrity of resulting data structures and should be therefore more efficient. Stochastic transformation operation mutation is also easily defined. Column tables can represent graphs with several output nodes and may be used e.g. for optimization of feed-forward neural networks. Simple illustrative examples of symbolic regression based on the column tables are presented.
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References
Handley, S., 1994, On the use of a directed acyclic graph to represent a population of computer programs, Proceedings of the 1994 IEEE World Congress on Computational Intelligence, IEEE Press.
Keijzer, M, 1996, Efficiently Representing Populations in Genetic Programming, Advances in Genetic Programming II, P.J. Angeline, K.E. Kinnear, eds., MIT Press. Cambridge, MA, pp. 259–278.
Zongker, D., and Punch, B., 1996, Program lil-gp, Michigan State University, obtainable from http://isl.cps.msu.edu/GA/software/lil-gp/
Hörner, H., 1996, The Vienna University of Economics Genetic Programming Kernel, Vienna University of Economics, obtainable from http://aif.wu-wien.ac.at/%7Egeyers/archive/gpk/
Glowacki, D., 1994, Geppetto: C Library for Writing Genetic Programming Applications, The University of Texas at Austin, obtainable from http://www-cgi.cs.cmu.edu/afs/cs.cmu.edu/project/ai-repository/ai/areas/genetic/gp/systems/geppetto/
Singleton, A., 1994, GPQUICK: Simple GP system implemented in C++, Creation Mechanics, Inc., PO Box 248, Peterborough, NH, obtainable from http://www-cgi.cs.cmu.edu/afs/cs.cmu.edu/project/ai-repository/ai/areas/genetic/gp/systems/gpquick/
Tackett, W. A., and Carmi, A., 1993, SGPC: Simple Genetic Programming in C, obtainable from http://www.cs.cmu.edu/afs/cs/project/ai-repository/ai/areas/genetic/gp/systems/sgpc/0.html
Fraser, A., 1994, Program gpc++, University of Salford, obtainable from http://www.salford.ac.uk/docs/depts/eee/genetic.html
Kvasnièka, V., Pospíchal, J., and Pelikán, M., 1996, Read’s linear codes and evolutionary computation over population of rooted trees, Intelligent Technologies, P. Sinèák, ed., vol. II, Her3/4any, Slovakia, November, pp. 141-154.
Pelikán, M., 1996, Genetic programming, student project (in Slovak), Faculty of Mathematics and Physics, Comenius University, Bratislava, Slovakia, April.
Read, R.C., 1972, Coding of Unlabeled Trees, Graph Theory and Computing, R.C. Read, ed., Academic Press, New York, pp. 153–182.
Harrary, F., 1969, Graph Theory, Addisson-Wesley, Reading, MA.
Koza, J. R., 1992, Genetic Programming: On the Programming of Computers by Means of Natural Selection, MIT Press, Cambridge, MA.
Koza, J.R., 1994, Genetic Programming (II): Automatic Discovery of Reusable Programs, MIT Press, Cambridge, MA.
Goldberg, D.E., 1989, Genetic Algorithms in Search, Optimization, Learning, Addison-Wesley, Reading, MA.
van Laarhoven, P.M.J., and Aarts, E.H.L., 1987, Simulated Annealing: Theory and Applications, Reidel, Dordrecht, The Netherlands.
Fogel, D.B., 1995, Evolutionary Computation: Toward a New Philosophy of Machine Intelligence. IEEE Press, Piscataway, NJ.
Teller, A., 1996, Evolving Programmers: The Co-evolution of Intelligent Recombination Operators, Advances in Genetic Programming II, P.J. Angeline and K.E. Kinnear, Jr, eds., MIT Press, Cambridge, MA, pp. 45–68.
Watson, J.D., Hopkins, N.H., Roberts, J.W., Wiener, A.M., 1987, Molecular Biology of the Gene, Menlo Park, CA: The Benjamin/Cummings Publishing Company, Inc.
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© 1998 Springer-Verlag London
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Kvasnièka, V., Pospíchal, J. (1998). Simple Implementation of Genetic Programming by Column Tables. In: Chawdhry, P.K., Roy, R., Pant, R.K. (eds) Soft Computing in Engineering Design and Manufacturing. Springer, London. https://doi.org/10.1007/978-1-4471-0427-8_6
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DOI: https://doi.org/10.1007/978-1-4471-0427-8_6
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