进化计算与可解释的人工智能:通往可理解的智能系统的路线图

IF 11.7 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Ryan Zhou, Jaume Bacardit, Alexander E. I. Brownlee, Stefano Cagnoni, Martin Fyvie, Giovanni Iacca, John McCall, Niki van Stein, David J. Walker, Ting Hu
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引用次数: 0

摘要

本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evolutionary Computation and Explainable AI: A Roadmap to Understandable Intelligent Systems
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来源期刊
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation 工程技术-计算机:理论方法
CiteScore
21.90
自引率
9.80%
发文量
196
审稿时长
3.6 months
期刊介绍: The IEEE Transactions on Evolutionary Computation is published by the IEEE Computational Intelligence Society on behalf of 13 societies: Circuits and Systems; Computer; Control Systems; Engineering in Medicine and Biology; Industrial Electronics; Industry Applications; Lasers and Electro-Optics; Oceanic Engineering; Power Engineering; Robotics and Automation; Signal Processing; Social Implications of Technology; and Systems, Man, and Cybernetics. The journal publishes original papers in evolutionary computation and related areas such as nature-inspired algorithms, population-based methods, optimization, and hybrid systems. It welcomes both purely theoretical papers and application papers that provide general insights into these areas of computation.
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