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Titlebook: Genetic Programming; Second European Work Riccardo Poli,Peter Nordin,Terence C. Fogarty Conference proceedings 1999 Springer-Verlag Berlin

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Automatic Generation of Affine IFS and Strongly Typed Genetic Programming applications. This paper describes a Strongly Typed Genetic Programming (STGP) approach to the automatic generation and evolution of 2D affine IFS, and affine maps in general. We explain the nature of the encoding used in conjunction with STGP, and demonstrate with examples its application to the inverse problem for IFS.
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Reactive and Memory-Based Genetic Programming for Robot Controldict reward based on state and action, which reduces the complexity of the evolved mappings. The work is motivated by applications to the control of autonomous robots. Preliminary results in software simulations indicate an enhanced learning speed and quality.
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Riccardo Poli,Peter Nordin,Terence C. FogartyIncludes supplementary material:
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https://doi.org/10.1007/978-3-476-03638-4aper we propose an evolutionary approach to this problem. We will focus on the representational issues, proposing alternative ways of codifying and interpreting Turing Machines, designed to take advantage of the existence of sets of equivalent Turing Machines. The experimental results show that thes
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,Tipps für den Kinderschockraum,resent a novel representation of function nodes, designed to allow the search operators to make smaller movements around the solution space. Using this representation, performance on the even-6-parity problem is improved by three orders of magnitude relative to the estimate given for standard GP in
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Die Zahlengerade unter dem Mikroskop,arallelism of sequential CPUs. In previous work [20] we have shown examples of applications of this technique to the evolution of parallel programs and to the parallel evaluation of 32 or 64 fitness cases per program execution in Boolean classification problems. After recalling the basic features of
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