Titlebook: Genetic Programming Theory and Practice XIV; Rick Riolo,Bill Worzel,Bill Tozier Book 2018 Springer Nature Switzerland AG 2018 Genetic prog

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978-3-030-07300-8Springer Nature Switzerland AG 2018

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Genetic Programming Theory and Practice XIV978-3-319-97088-2Series ISSN 1932-0167 Series E-ISSN 1932-0175

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PRETSL: Distributed Probabilistic Rule Evolution for Time-Series Classification, rule sets. The method is tested on 20 UCI data problems, as well as a larger dataset of arterial blood pressure waveforms. Results show consistent improvement in all cases compared to binary classification rule-sets.

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Similarity-Based Analysis of Population Dynamics in Genetic Programming Performing Symbolic Regressmilarity measures to investigate the evolution of diversity in three GP algorithmic flavors: standard GP, offspring selection GP (OS-GP), and age-layered population structure GP (ALPS-GP). Empirical measurements on two symbolic regression benchmark problems reveal important differences between the d

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An Investigation of Hybrid Structural and Behavioral Diversity Methods in Genetic Programming,chniques have been proposed for combating premature convergence and improving search efficiency in genetic programming. Recent research has shown that while genetic diversity is important, focusing directly on sustaining behavioral diversity may be more beneficial. These two related areas have recei

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Linear Genomes for Structured Programs,e hierarchical structure of computer programs and the syntactic constraints that they must obey, it is difficult to implement variation operators that affect different parts of programs with uniform probability. This lack of uniformity can have detrimental effects on evolutionary search, such as inc