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Titlebook: Genetic Programming; 8th European Confere Maarten Keijzer,Andrea Tettamanzi,Marco Tomassini Conference proceedings 2005 Springer-Verlag Ber

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Genetic Transposition in Tree-Adjoining Grammar Guided Genetic Programming: The Duplication Operatoras a generic local search operator, however, it helped TAG3P not only to solve the problems reliably but also cope well with scalability in problem complexity. Moreover, it managed to solve problems with very small population sizes.
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Operator-Based Distance for Genetic Programming: Subtree Crossover Distancerator-based edit distance measures. In particular, we focus on the subtree crossover operator. An empirical study is presented to illustrate the features of an operator-based distance. This paper makes progress toward improved algorithmic analysis by using appropriate measures of distance and similarity.
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The Tree-String Problem: An Artificial Domain for Structure and Content Search several benefits, including: the direct control of both structure and content objectives, the production of a rich and representative search space, the ability to create tunably difficult and random instances and the flexibility for specialisation.
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Automated Re-invention of a Previously Patented Optical Lens System Using Genetic Programmingly, genetic programming created an optical system that infringed a previous patent (the Konig patent) and improved upon another previous patent (the Tackaberry-Muller patent). The genetically evolved design is an example of a human-competitive result produced by genetic programming in the field of optical design.
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Evolving L-Systems to Capture Protein Structure Native Conformationsto find a set of rewriting rules that represents a target native structure on the lattice model. The proposed approach has produced promising results for short sequences. Thus the foundations are set for a novel encoding based on L-systems for evolutionary approaches to both the Protein Structure Prediction and Inverse Folding Problems.
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Tarpeian Bloat Control and Generalization Accuracylic regression. The results are contrasted, showing that it can either increase or reduce the generalization power of GP hypotheses, depending on the problem at hand. Experiments also confirm the decrease in size of programs. We conclude that Tarpeian Control might be useful if carefully tuned to the problem at hand.
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