Errata: Convergence Analysis of Evolutionary Algorithms That Are Based on the Paradigm of Information Geometry

IF 4.6 2区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Evolutionary Computation Pub Date : 2020-12-02 DOI:10.1162/evco_x_00281
Hans-Georg Beyer
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勘误表:基于信息几何范式的进化算法的收敛性分析
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来源期刊
Evolutionary Computation
Evolutionary Computation 工程技术-计算机:理论方法
CiteScore
6.40
自引率
1.50%
发文量
20
审稿时长
3 months
期刊介绍: Evolutionary Computation is a leading journal in its field. It provides an international forum for facilitating and enhancing the exchange of information among researchers involved in both the theoretical and practical aspects of computational systems drawing their inspiration from nature, with particular emphasis on evolutionary models of computation such as genetic algorithms, evolutionary strategies, classifier systems, evolutionary programming, and genetic programming. It welcomes articles from related fields such as swarm intelligence (e.g. Ant Colony Optimization and Particle Swarm Optimization), and other nature-inspired computation paradigms (e.g. Artificial Immune Systems). As well as publishing articles describing theoretical and/or experimental work, the journal also welcomes application-focused papers describing breakthrough results in an application domain or methodological papers where the specificities of the real-world problem led to significant algorithmic improvements that could possibly be generalized to other areas.
期刊最新文献
Tail Bounds on the Runtime of Categorical Compact Genetic Algorithm. Optimizing Monotone Chance-Constrained Submodular Functions Using Evolutionary Multi-Objective Algorithms. Genetic Programming for Automatically Evolving Multiple Features to Classification. A Tri-Objective Method for Bi-Objective Feature Selection in Classification. Preliminary Analysis of Simple Novelty Search.
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