下船
发表于 2025-3-26 21:16:11
A Metric for Genetic Programs and Fitness Sharing applying fitness sharing to genetic programs, in analogy with fitness sharing applied to genetic algorithms. The experimental results for several parameter settings are discussed. We observe that by applying fitness sharing the code growth of genetic programs could be limited.
外表读作
发表于 2025-3-27 02:21:08
978-3-540-67339-2Springer-Verlag Berlin Heidelberg 2000
epidermis
发表于 2025-3-27 07:53:49
Genetic Programming978-3-540-46239-2Series ISSN 0302-9743 Series E-ISSN 1611-3349
BUOY
发表于 2025-3-27 12:59:11
On the Impact of the Representation on Fitness Landscapes we believe to be generic of standard GP, we show that the way individuals are coded is an essential concept which impacts the fitness landscape. We give evidence that the ruggedness of the landscape affects the behavior of the algorithm and we find that, below a critical population, whose size is r
失眠症
发表于 2025-3-27 17:23:58
The Legion System: A Novel Approach to Evolving Heterogeneity for Collective Problem Solvinglutionary control. Two task domains are studied: solutions are evolved for the two tasks using an evolutionary algorithm called the Legion system. A new metric of heterogeneity is also introduced, which measures the heterogeneity of any evolved group behaviour. It was found that the amount of hetero
OUTRE
发表于 2025-3-27 21:37:07
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Volatile-Oils
发表于 2025-3-28 00:32:52
Register Based Genetic Programming on FPGA Computing Platformson of micro architectural and instruction design issues not normally possible when using classical Von Neumann machines. More importantly, the desirability of minimising memory management overheads results in the imposition of additional constraints to the crossover operator. Specifically, individua
荧光
发表于 2025-3-28 04:09:24
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aggrieve
发表于 2025-3-28 06:34:12
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custody
发表于 2025-3-28 12:56:08
Evolution of a Controller with a Free Variable Using Genetic ProgrammingFor example, the familiar formula for solving a quadratic equation contains free variables representing the equation’s coefficients. Previous work has demonstrated that genetic programming can automatically synthesize the design for a controller consisting of a topological arrangement of signal proc