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Titlebook: Genetic Programming; 18th European Confer Penousal Machado,Malcolm I. Heywood,Kevin Sim Conference proceedings 2015 Springer International

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发表于 2025-3-21 19:39:13 | 显示全部楼层 |阅读模式
书目名称Genetic Programming
副标题18th European Confer
编辑Penousal Machado,Malcolm I. Heywood,Kevin Sim
视频videohttp://file.papertrans.cn/383/382585/382585.mp4
概述Includes supplementary material:
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Genetic Programming; 18th European Confer Penousal Machado,Malcolm I. Heywood,Kevin Sim Conference proceedings 2015 Springer International
描述This book constitutes the refereed proceedings of the 18th European Conference on Genetic Programming, EuroGP 2015, held in Copenhagen, Spain, in April 2015 co-located with the Evo 2015 events, EvoCOP, Evo MUSART and Evo Applications. The 12 revised full papers presented together with 6 poster papers were carefully reviewed and selected form 36 submissions. The wide range of topics in this volume reflects the current state of research in the field. Thus, we see topics as diverse as semantic methods, recursive programs, grammatical methods, coevolution, Cartesian GP, feature selection, initialisation procedures, ensemble methods and search objectives; and applications including text processing, cryptography, numerical modelling, software parallelisation, creation and optimisation of circuits, multi-class classification, scheduling and artificial intelligence.
出版日期Conference proceedings 2015
关键词Artificial intelligence; Automatic programming; Cartesian genetic programming; Circuit design; Evolution
版次1
doihttps://doi.org/10.1007/978-3-319-16501-1
isbn_softcover978-3-319-16500-4
isbn_ebook978-3-319-16501-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing Switzerland 2015
The information of publication is updating

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Automatic Derivation of Search Objectives for Test-Based Genetic Programmingpassed. We posit that scrutinizing the outcomes of programs’ interactions with individual tests may help making program synthesis more effective. To this aim, we propose DOC, a method that autonomously derives new search objectives by clustering the outcomes of interactions between programs in the p
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Evolutionary Design of Transistor Level Digital Circuits Using Discrete Simulationder to improve the time consuming evaluation of candidate solutions, a discrete event-driven simulator was introduced. The proposed simulator operates on multiple logic levels to achieve reasonable trade-off between performance and precision. A suitable level of abstraction reflecting the behaviour
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Attributed Grammatical Evolution Using Shared Memory Spaces and Dynamically Typed Semantic Function grammars (AG). We discuss the motivations behind our system design, from its use of shared memory spaces for attribute storage to the use of a dynamically type programming language, Python, to specify grammar semantics..After a brief analysis of some of the existing GE AG system we outline two sets
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Indirectly Encoded Fitness Predictors Coevolved with Cartesian Programsor (TOV) evaluations, needed to obtain a satisfactory solution, to reduce the computational cost of evolution. This paper introduces the use of coevolution of fitness predictors in CGP with a new type of indirectly encoded predictors. Indirectly encoded predictors are operated using the CGP and prov
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