Why is the Rescorla-Wagner model so influential?

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Fabian A. Soto , Edgar H. Vogel , Yerco E. Uribe-Bahamonde , Omar D. Perez
{"title":"Why is the Rescorla-Wagner model so influential?","authors":"Fabian A. Soto ,&nbsp;Edgar H. Vogel ,&nbsp;Yerco E. Uribe-Bahamonde ,&nbsp;Omar D. Perez","doi":"10.1016/j.nlm.2023.107794","DOIUrl":null,"url":null,"abstract":"<div><p>The influence of the Rescorla-Wagner model cannot be overestimated, despite that (1) the model does not differ much computationally from its predecessors and competitors, and (2) its shortcomings are well-known in the learning community. Here we discuss the reasons behind its widespread influence in the cognitive and neural sciences, and argue that it is the constant search for general-process theories by learning scholars which eventually produced a model whose application spans many different areas of research to this day. We focus on the theoretical and empirical background of the model, the theoretical connections that it has with later developments across Marr’s levels of analysis, as well as the broad variety of research that it has guided and inspired.</p></div>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"102","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1074742723000758","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0

Abstract

The influence of the Rescorla-Wagner model cannot be overestimated, despite that (1) the model does not differ much computationally from its predecessors and competitors, and (2) its shortcomings are well-known in the learning community. Here we discuss the reasons behind its widespread influence in the cognitive and neural sciences, and argue that it is the constant search for general-process theories by learning scholars which eventually produced a model whose application spans many different areas of research to this day. We focus on the theoretical and empirical background of the model, the theoretical connections that it has with later developments across Marr’s levels of analysis, as well as the broad variety of research that it has guided and inspired.

为什么Rescorla Wagner模型如此有影响力?
Rescorla Wagner模型的影响怎么估计都不为过,尽管(1)该模型在计算上与其前身和竞争对手没有太大区别,(2)其缺点在学习界是众所周知的。在这里,我们讨论了它在认知科学和神经科学中广泛影响的原因,并认为正是学习学者对一般过程理论的不断探索,最终产生了一个模型,该模型的应用至今跨越了许多不同的研究领域。我们重点关注该模型的理论和实证背景,它与马尔分析水平的后期发展之间的理论联系,以及它所指导和启发的广泛研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信