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Titlebook: Genetic Programming; 9th European Confere Pierre Collet,Marco Tomassini,Anikó Ekárt Conference proceedings 2006 Springer-Verlag Berlin Heid

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Konsequenzen: Schuld und Strafe, scheduling, where the next state of the system is determined based on priority values of certain system elements. The evolved solutions are compared with existing scheduling heuristics for single machine dynamic problem and job shop scheduling with bottleneck estimation.
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https://doi.org/10.1007/11729976adaptive systems; classification; complexity; design; evolution; evolutionary algorithms; evolutionary opt
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Ulrich Jordan,Birgit Külpp,Ines Bruckschenild which is then passed into the next generation..We have tested its performance on many benchmark problems. It has shown better results than the standard GP crossover operator, using either the same number or fewer individual evaluations. Furthermore, the average fitness of populations using this
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https://doi.org/10.1007/978-3-642-86046-1, uses tree-based GP to generate and evaluate approximate query candidates, automatically. We highlight and discuss various avenues of exploration and evaluate the success of our experiments based on the speed, cost, and accuracy of the results retrieved by the re-formulated (GP generated) queries a
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https://doi.org/10.1007/978-3-322-96287-4 an IPO Underpricing prediction domain (a classical regression problem) is confronted. Our method obtained in both cases competitive results and, in addition, it drastically reduced dimensionality of the problem.
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AQUAGP: Approximate QUery Answers Using Genetic Programming, uses tree-based GP to generate and evaluate approximate query candidates, automatically. We highlight and discuss various avenues of exploration and evaluate the success of our experiments based on the speed, cost, and accuracy of the results retrieved by the re-formulated (GP generated) queries a
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