Abstract
For many years the field of Genetic Algorithms (GAs) has been dominated by bit-string based GAs. The argument as to why bit-strings are the best method of encoding parameters in GA strings is known as the principle of minimal alphabet.
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Bibliography
Caruana R.A. and Schaffer J.D., Representation and Hidden Bias: Gray vs. Binary Coding for Genetic Algorithms, Proc. Fifth International Conference on Machine Learning, 153 (1988).
Davis L., Adapting Operator Probabilities in Genetic Algorithms, Proc. Third International Conference on Genetic Algorithms, 61 (1989).
Gibson G.M., Application of Genetic Algorithms to Mixed Schedule and Parameter Optimisation for a Visual Interactive Modeller, Proc. Fifth Workshop on Neural Networks, 119 (1993a).
Gibson G.M., A Genetic Algorithm for Optimising Problems with Embedded Design Decisions, Proc. 6th Australian Joint Conference on Artificial Intelligence, 99 (1993b).
Goldberg D.E., Genetic Algorithms in Search, Optimisation & Machine Learning, Addison-Wesley, New York NY, (1989).
Grefenstette J.J. and Baker J.E., How Genetic Algorithms Work: A Critical Look at Implicit Parallelism, Proc. Third International Conference on Genetic Algorithms, 20 (1989).
Holland J.H., Adaptation in Natural and Artificial Systems, Ann Arbor: The University of Michigan Press, (1975).
Holland J.H., Adaptation in Natural and Artificial Systems, MIT Press, (1993).
Koza J.R. 1992, Genetic Programming: On the Programming of Computers by Means of Natural Selection, MIT Press.
Levenick J.R., Inserting Introns Improves Genetic Algorithm Success Rate: Taking a Cue from Biology, Proc. Fourth International Conference on Genetic Algorithms, 123 (1991).
Wills C., The Wisdom of the Genes, Basic Books, New York, (1989).
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Gibson, G.M. (1995). An Argument Against the Principle of Minimal Alphabet. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-7535-4_41
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DOI: https://doi.org/10.1007/978-3-7091-7535-4_41
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