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Titlebook: Applications of Evolutionary Computation; EvoApplications 2010 Cecilia Chio,Stefano Cagnoni,Georgios N. Yannakaki Conference proceedings 20

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期刊全稱Applications of Evolutionary Computation
期刊簡稱EvoApplications 2010
影響因子2023Cecilia Chio,Stefano Cagnoni,Georgios N. Yannakaki
視頻videohttp://file.papertrans.cn/160/159390/159390.mp4
發(fā)行地址Fast track conference proceeding.Unique visibility.State of the art research
學(xué)科分類Lecture Notes in Computer Science
圖書封面Titlebook: Applications of Evolutionary Computation; EvoApplications 2010 Cecilia Chio,Stefano Cagnoni,Georgios N. Yannakaki Conference proceedings 20
影響因子Evolutionary Computation (EC) techniques are e?cient, nature-inspired me- ods based on the principles of natural evolution and genetics. Due to their - ciency and simple underlying principles, these methods can be used for a diverse rangeofactivitiesincludingproblemsolving,optimization,machinelearningand pattern recognition. A large and continuously increasing number of researchers and professionals make use of EC techniques in various application domains. This volume presents a careful selection of relevant EC examples combined with a thorough examination of the techniques used in EC. The papers in the volume illustrate the current state of the art in the application of EC and should help and inspire researchers and professionals to develop e?cient EC methods for design and problem solving. All papers in this book were presented during EvoApplications 2010, which included a range of events on application-oriented aspects of EC. Since 1998, EvoApplications — formerly known as EvoWorkshops— has provided a unique opportunity for EC researchers to meet and discuss application aspects of EC and has been an important link between EC research and its application in a variety of domains.
Pindex Conference proceedings 2010
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Reference work 2020Latest editionnew behaviors and increase in complexity over time. It would be highly desirable to establish the necessary and sufficient conditions which lead to such an arms race. We investigate what these conditions may be using a model of competitive coevolution. Coevolving species are modeled as points which
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Big C Versus Little c Creativity,he selfish objective to reach its destination in the shortest time possible, and a preference in terms of paths to take, based on the presence of other agents and on the width of the roads. Those parameters are changed with an evolutionary strategy, to mimic the adaptation of a human driver to diffe
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