Titlebook: Genetic Programming Theory and Practice IV; Rick Riolo,Terence Soule,Bill Worzel Book 2007 Springer-Verlag US 2007 Automat.Boosting.algori

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Incumbent

Boosting Improves Stability and Accuracy of Genetic Programming in Biological Sequence Classificatiassifiers to bagging and boosting with crossvalidation and parameter optimization requires more computing power. A special-purpose search processor for fitness evaluation renders boosted genetic programming practical for our purposes.

exigent

Design of Posynomial Models for Mosfets: Symbolic Regression Using Genetic Algorithms,xpressions for a circuit’s performance measurements. We show how a genetic algorithm can be exploited to evolve a posynomial expression (i.e. model) of transistor (i.e. mosfet) behavior more accurately than statistical techniques in the literature.

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線

978-1-4419-4123-7Springer-Verlag US 2007

FAZE

Genetic Programming Theory and Practice IV978-0-387-49650-4Series ISSN 1932-0167 Series E-ISSN 1932-0175

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https://doi.org/10.1007/978-3-030-54913-8 propose majority voting technique for the prediction of the class of a test sample. In the application to robotics, we use GP to generate the motion sequences of humanoid robots. We introduce an integrated approach, i.e., the combination of GP and reinforcement learning, to design the desirable mot