A Dual Simple Recurrent Network Model for Chunking and Abstract Processes in Sequence Learning
文献类型:期刊论文
作者 | Wang, Lituan1; Feng, Yangqin1,2; Fu, Qiufang3,4; Wang, Jianyong1; Sun, Xunwei3,4; Fu, Xiaolan3,4; Zhang, Lei1; Yi, Zhang1 |
刊名 | FRONTIERS IN PSYCHOLOGY |
出版日期 | 2021-05-04 |
卷号 | 12页码:17 |
ISSN号 | 1664-1078 |
关键词 | sequence learning abstract processes chunking processes simple recurrent network dual simple recurrent |
DOI | 10.3389/fpsyg.2021.587405 |
产权排序 | 3 |
文献子类 | 实证研究 |
英文摘要 | Although many studies have provided evidence that abstract knowledge can be acquired in artificial grammar learning, it remains unclear how abstract knowledge can be attained in sequence learning. To address this issue, we proposed a dual simple recurrent network (DSRN) model that includes a surface SRN encoding and predicting the surface properties of stimuli and an abstract SRN encoding and predicting the abstract properties of stimuli. The results of Simulations 1 and 2 showed that the DSRN model can account for learning effects in the serial reaction time (SRT) task under different conditions, and the manipulation of the contribution weight of each SRN accounted for the contribution of conscious and unconscious processes in inclusion and exclusion tests in previous studies. The results of human performance in Simulation 3 provided further evidence that people can implicitly learn both chunking and abstract knowledge in sequence learning, and the results of Simulation 3 confirmed that the DSRN model can account for how people implicitly acquire the two types of knowledge in sequence learning. These findings extend the learning ability of the SRN model and help understand how different types of knowledge can be acquired implicitly in sequence learning. |
WOS关键词 | IMPLICIT TRANSFER ; KNOWLEDGE ; EXPLICIT ; ACQUISITION ; PERFORMANCE ; AWARENESS |
资助项目 | National Key Research and Development Programme of China[2018AAA0100205] ; National Natural Science Foundation of China[61632004] ; National Natural Science Foundation of China[61772353] ; National Natural Science Foundation of China[NSFC 61621136008/DFG TRR-169] ; German Research Foundation[NSFC 61621136008/DFG TRR-169] |
WOS研究方向 | Psychology |
语种 | 英语 |
出版者 | FRONTIERS MEDIA SA |
WOS记录号 | WOS:000651222500001 |
源URL | [http://ir.psych.ac.cn/handle/311026/39305] |
专题 | 心理研究所_脑与认知科学国家重点实验室 |
通讯作者 | Fu, Qiufang |
作者单位 | 1.Sichuan Univ, Coll Comp Sci, Machine Intelligence Lab, Chengdu, Peoples R China 2.Agcy Sci Technol & Res, Inst High Performance Comp, Singapore, Singapore 3.Chinese Acad Sci, Inst Psychol, State Key Lab Brain & Cognit Sci, Beijing, Peoples R China 4.Univ Chinese Acad Sci, Dept Psychol, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Wang, Lituan,Feng, Yangqin,Fu, Qiufang,et al. A Dual Simple Recurrent Network Model for Chunking and Abstract Processes in Sequence Learning[J]. FRONTIERS IN PSYCHOLOGY,2021,12:17. |
APA | Wang, Lituan.,Feng, Yangqin.,Fu, Qiufang.,Wang, Jianyong.,Sun, Xunwei.,...&Yi, Zhang.(2021).A Dual Simple Recurrent Network Model for Chunking and Abstract Processes in Sequence Learning.FRONTIERS IN PSYCHOLOGY,12,17. |
MLA | Wang, Lituan,et al."A Dual Simple Recurrent Network Model for Chunking and Abstract Processes in Sequence Learning".FRONTIERS IN PSYCHOLOGY 12(2021):17. |
入库方式: OAI收割
来源:心理研究所
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