生成式对抗网络GAN的研究进展与展望
王坤峰1,2; 苟超1,3; 段艳杰1,3; 林懿伦1,3; 郑心湖4; 王飞跃1,5
Source Publication自动化学报
2017-03
Volume43Issue:3Pages:321¡332
Other AbstractGenerative adversarial networks (GANs) have become a hot research topic in artiflcial intelligence. Inspired by the two-player zero-sum game, GAN is composed of a generator and a discriminator, both trained with the adversarial learning mechanism. The aim of GAN is to estimate the potential distribution of existing data and generate new data samples from the same distribution. Since its initiation, GAN has been widely studied due to its enormous prospect for applications, including image and vision computing, speech and language processing, information security, and chess game. In this paper we summarize the state of the art of GAN and look into its future. First of all, we survey the GAN's background, theoretic and implementation models, application flelds, advantages and disadvantages, and development trends. Then, we investigate the relation between GAN and parallel intelligence with the conclusion that GAN has a great potential in parallel systems especially in computational experiments, in terms of virtual-real interaction and integration. Finally, we clarify that GAN can provide speciflc and substantial algorithmic support for the ACP theory.
Keyword生成式对抗网络 生成式模型 零和博弈 对抗学习 平行智能 Acp 方法
DOI10.16383/j.aas.2017.y000003
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/20218
Collection复杂系统管理与控制国家重点实验室_先进控制与自动化
Affiliation1.中国科学院自动化研究所
2.青岛智能产业技术研究院
3.中国科学院大学
4.明尼苏达大学
5.国防科学技术大学
Recommended Citation
GB/T 7714
王坤峰,苟超,段艳杰,等. 生成式对抗网络GAN的研究进展与展望[J]. 自动化学报,2017,43(3):321¡332.
APA 王坤峰,苟超,段艳杰,林懿伦,郑心湖,&王飞跃.(2017).生成式对抗网络GAN的研究进展与展望.自动化学报,43(3),321¡332.
MLA 王坤峰,et al."生成式对抗网络GAN的研究进展与展望".自动化学报 43.3(2017):321¡332.
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