创造力与机器学习：一项调查

IF 23.8 1区计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS

ACM Computing Surveys Pub Date : 2024-05-11 DOI:10.1145/3664595

Giorgio Franceschelli, Mirco Musolesi

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引用次数: 0

摘要

人们对机器学习和创造力领域的兴趣与日俱增。本调查报告概述了计算创造力理论、关键机器学习技术（包括生成式深度学习）以及相应的自动评估方法的历史和现状。在对该领域的主要贡献进行批判性讨论之后，我们概述了该领域当前的研究挑战和新出现的机遇。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Creativity and Machine Learning: A Survey

There is a growing interest in the area of machine learning and creativity. This survey presents an overview of the history and the state of the art of computational creativity theories, key machine learning techniques (including generative deep learning), and corresponding automatic evaluation methods. After presenting a critical discussion of the key contributions in this area, we outline the current research challenges and emerging opportunities in this field.

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来源期刊

ACM Computing Surveys 工程技术-计算机：理论方法

CiteScore

33.20

自引率

0.60%

发文量

372

审稿时长

12 months

期刊介绍： ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.