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Genetic Algorithms

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The article was published on 2002-01-01 and is currently open access. It has received 17039 citations till now.

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Citations
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Evolutionary programming as a platform for in silico metabolic engineering

TL;DR: An evolutionary programming based method to rapidly identify gene deletion strategies for optimization of a desired phenotypic objective function is reported and shows that evolutionary programming enables solving large gene knockout problems in relatively short computational time.
Journal ArticleDOI

A Method for Constructing a Social Vulnerability Index: An Application to Hurricane Storm Surges in a Developed Country

TL;DR: The paper concludes that it is possible to construct an effective index of vulnerability without weighting the individual vulnerability indicators.
Journal ArticleDOI

Information-seeking, curiosity, and attention: computational and neural mechanisms

TL;DR: Eye movements reflect visual information searching in multiple conditions and are amenable for cellular-level investigations, which suggests that the oculomotor system is an excellent model system for understanding information-sampling mechanisms.
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Flower pollination algorithm: A novel approach for multiobjective optimization

TL;DR: A comparison of the proposed algorithm with other algorithms has been made, which shows that the FPA is efficient with a good convergence rate, and the importance for further parametric studies and theoretical analysis is highlighted and discussed.
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Procedural content generation for games: A survey

TL;DR: This is the first comprehensive survey of the field of PCG-G, and introduces a comprehensive, six-layered taxonomy of game content: bits, space, systems, scenarios, design, and derived.
References
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Book

Genetic algorithms in search, optimization, and machine learning

TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Book

Genetic Algorithms + Data Structures = Evolution Programs

TL;DR: GAs and Evolution Programs for Various Discrete Problems, a Hierarchy of Evolution Programs and Heuristics, and Conclusions.
Journal ArticleDOI

An Introduction to Genetic Algorithms.

TL;DR: An Introduction to Genetic Algorithms as discussed by the authors is one of the rare examples of a book in which every single page is worth reading, and the author, Melanie Mitchell, manages to describe in depth many fascinating examples as well as important theoretical issues.
Book

Handbook of Genetic Algorithms

TL;DR: This book sets out to explain what genetic algorithms are and how they can be used to solve real-world problems, and introduces the fundamental genetic algorithm (GA), and shows how the basic technique may be applied to a very simple numerical optimisation problem.
Journal ArticleDOI

An Introduction to Population Genetics Theory

James F. Crow, +1 more
- 01 Sep 1971 - 
TL;DR: An introduction to population genetics theory, An introduction to Population Genetics Theory, Population Genetics theory, Population genetics theory as discussed by the authors, Population genetics, population genetics, and population genetics theories, Population Genetic Theory