{"title":"学习和记忆密不可分。","authors":"Sue Llewellyn","doi":"10.1017/S0140525X2400013X","DOIUrl":null,"url":null,"abstract":"<p><p>The authors' aim is to build \"more biologically plausible learning algorithms\" that work in naturalistic environments. Given that, first, human learning and memory are inextricable, and, second, that much human learning is unconscious, can the authors' first research question of how people improve their learning abilities over time be answered without addressing these two issues? I argue that it cannot.</p>","PeriodicalId":16,"journal":{"name":"ACS Energy Letters ","volume":null,"pages":null},"PeriodicalIF":19.3000,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Learning and memory are inextricable.\",\"authors\":\"Sue Llewellyn\",\"doi\":\"10.1017/S0140525X2400013X\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The authors' aim is to build \\\"more biologically plausible learning algorithms\\\" that work in naturalistic environments. Given that, first, human learning and memory are inextricable, and, second, that much human learning is unconscious, can the authors' first research question of how people improve their learning abilities over time be answered without addressing these two issues? I argue that it cannot.</p>\",\"PeriodicalId\":16,\"journal\":{\"name\":\"ACS Energy Letters \",\"volume\":null,\"pages\":null},\"PeriodicalIF\":19.3000,\"publicationDate\":\"2024-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Energy Letters \",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://doi.org/10.1017/S0140525X2400013X\",\"RegionNum\":1,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, PHYSICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Energy Letters ","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1017/S0140525X2400013X","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
The authors' aim is to build "more biologically plausible learning algorithms" that work in naturalistic environments. Given that, first, human learning and memory are inextricable, and, second, that much human learning is unconscious, can the authors' first research question of how people improve their learning abilities over time be answered without addressing these two issues? I argue that it cannot.
ACS Energy Letters Energy-Renewable Energy, Sustainability and the Environment
CiteScore
31.20
自引率
5.00%
发文量
469
审稿时长
1 months
期刊介绍:
ACS Energy Letters is a monthly journal that publishes papers reporting new scientific advances in energy research. The journal focuses on topics that are of interest to scientists working in the fundamental and applied sciences. Rapid publication is a central criterion for acceptance, and the journal is known for its quick publication times, with an average of 4-6 weeks from submission to web publication in As Soon As Publishable format.
ACS Energy Letters is ranked as the number one journal in the Web of Science Electrochemistry category. It also ranks within the top 10 journals for Physical Chemistry, Energy & Fuels, and Nanoscience & Nanotechnology.
The journal offers several types of articles, including Letters, Energy Express, Perspectives, Reviews, Editorials, Viewpoints and Energy Focus. Additionally, authors have the option to submit videos that summarize or support the information presented in a Perspective or Review article, which can be highlighted on the journal's website. ACS Energy Letters is abstracted and indexed in Chemical Abstracts Service/SciFinder, EBSCO-summon, PubMed, Web of Science, Scopus and Portico.