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Behavioral and Brain Sciences最新文献

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The added value of affective processes for models of human cognition and learning. 情感过程对人类认知和学习模型的附加值。
IF 16.6 1区 心理学
Behavioral and Brain Sciences Pub Date : 2024-09-23 DOI: 10.1017/S0140525X24000207
Yoann Stussi, Daniel Dukes, David Sander
{"title":"The added value of affective processes for models of human cognition and learning.","authors":"Yoann Stussi, Daniel Dukes, David Sander","doi":"10.1017/S0140525X24000207","DOIUrl":"https://doi.org/10.1017/S0140525X24000207","url":null,"abstract":"<p><p>Building on the affectivism approach, we expand on Binz et al.'s meta-learning research program by highlighting that emotion and other affective phenomena should be key to the modeling of human learning. We illustrate the added value of affective processes for models of learning across multiple domains with a focus on reinforcement learning, knowledge acquisition, and social learning.</p>","PeriodicalId":8698,"journal":{"name":"Behavioral and Brain Sciences","volume":null,"pages":null},"PeriodicalIF":16.6,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142279936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Integrative learning in the lens of meta-learned models of cognition: Impacts on animal and human learning outcomes. 元学习认知模型视角下的综合学习：对动物和人类学习成果的影响。
IF 16.6 1区 心理学
Behavioral and Brain Sciences Pub Date : 2024-09-23 DOI: 10.1017/S0140525X2400027X
Bin Yin, Xi-Dan Xiao, Xiao-Rui Wu, Rong Lian
{"title":"Integrative learning in the lens of meta-learned models of cognition: Impacts on animal and human learning outcomes.","authors":"Bin Yin, Xi-Dan Xiao, Xiao-Rui Wu, Rong Lian","doi":"10.1017/S0140525X2400027X","DOIUrl":"https://doi.org/10.1017/S0140525X2400027X","url":null,"abstract":"<p><p>This commentary examines the synergy between meta-learned models of cognition and integrative learning in enhancing animal and human learning outcomes. It highlights three integrative learning modes - holistic integration of parts, top-down reasoning, and generalization with in-depth analysis - and their alignment with meta-learned models of cognition. This convergence promises significant advances in educational practices, artificial intelligence, and cognitive neuroscience, offering a novel perspective on learning and cognition.</p>","PeriodicalId":8698,"journal":{"name":"Behavioral and Brain Sciences","volume":null,"pages":null},"PeriodicalIF":16.6,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142279920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Meta-learning and the evolution of cognition. 元学习与认知进化。
IF 16.6 1区 心理学
Behavioral and Brain Sciences Pub Date : 2024-09-23 DOI: 10.1017/S0140525X24000177
Walter Veit, Heather Browning
{"title":"Meta-learning and the evolution of cognition.","authors":"Walter Veit, Heather Browning","doi":"10.1017/S0140525X24000177","DOIUrl":"https://doi.org/10.1017/S0140525X24000177","url":null,"abstract":"<p><p>Meta-learning offers a promising framework to make sense of some parts of decision-making that have eluded satisfactory explanation. Here, we connect this research to work in animal behaviour and cognition in order to shed light on how and whether meta-learning could help us to understand the evolution of cognition.</p>","PeriodicalId":8698,"journal":{"name":"Behavioral and Brain Sciences","volume":null,"pages":null},"PeriodicalIF":16.6,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142279926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Linking meta-learning to meta-structure. 将元学习与元结构联系起来。
IF 16.6 1区 心理学
Behavioral and Brain Sciences Pub Date : 2024-09-23 DOI: 10.1017/S0140525X24000232
Malte Schilling, Helge J Ritter, Frank W Ohl
{"title":"Linking meta-learning to meta-structure.","authors":"Malte Schilling, Helge J Ritter, Frank W Ohl","doi":"10.1017/S0140525X24000232","DOIUrl":"10.1017/S0140525X24000232","url":null,"abstract":"<p><p>We propose that a principled understanding of meta-learning, as aimed for by the authors, benefits from linking the focus on learning with an equally strong focus on structure, which means to address the question: What are the meta-structures that can guide meta-learning?</p>","PeriodicalId":8698,"journal":{"name":"Behavioral and Brain Sciences","volume":null,"pages":null},"PeriodicalIF":16.6,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142279923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The meta-learning toolkit needs stronger constraints. 元学习工具包需要更强的约束。
IF 16.6 1区 心理学
Behavioral and Brain Sciences Pub Date : 2024-09-23 DOI: 10.1017/S0140525X24000104
Erin Grant
{"title":"The meta-learning toolkit needs stronger constraints.","authors":"Erin Grant","doi":"10.1017/S0140525X24000104","DOIUrl":"https://doi.org/10.1017/S0140525X24000104","url":null,"abstract":"<p><p>The implementation of meta-learning targeted by Binz et al. inherits benefits and drawbacks from its nature as a connectionist model. Drawing from historical debates around bottom-up and top-down approaches to modeling in cognitive science, we should continue to bridge levels of analysis by constraining meta-learning and meta-learned models with complementary evidence from across the cognitive and computational sciences.</p>","PeriodicalId":8698,"journal":{"name":"Behavioral and Brain Sciences","volume":null,"pages":null},"PeriodicalIF":16.6,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142279938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Probabilistic programming versus meta-learning as models of cognition. 作为认知模型的概率编程与元学习。
IF 16.6 1区 心理学
Behavioral and Brain Sciences Pub Date : 2024-09-23 DOI: 10.1017/S0140525X24000153
Desmond C Ong, Tan Zhi-Xuan, Joshua B Tenenbaum, Noah D Goodman
{"title":"Probabilistic programming versus meta-learning as models of cognition.","authors":"Desmond C Ong, Tan Zhi-Xuan, Joshua B Tenenbaum, Noah D Goodman","doi":"10.1017/S0140525X24000153","DOIUrl":"10.1017/S0140525X24000153","url":null,"abstract":"<p><p>We summarize the recent progress made by probabilistic programming as a unifying formalism for the probabilistic, symbolic, and data-driven aspects of human cognition. We highlight differences with meta-learning in flexibility, statistical assumptions and inferences about cogniton. We suggest that the meta-learning approach could be further strengthened by considering Connectionist <i>and</i> Bayesian approaches, rather than exclusively one or the other.</p>","PeriodicalId":8698,"journal":{"name":"Behavioral and Brain Sciences","volume":null,"pages":null},"PeriodicalIF":16.6,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142279933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The reinforcement metalearner as a biologically plausible meta-learning framework. 强化金属学习器作为一种生物学上可信的元学习框架。
IF 16.6 1区 心理学
Behavioral and Brain Sciences Pub Date : 2024-09-23 DOI: 10.1017/S0140525X24000219
Tim Vriens, Mattias Horan, Jacqueline Gottlieb, Massimo Silvetti
{"title":"The reinforcement metalearner as a biologically plausible meta-learning framework.","authors":"Tim Vriens, Mattias Horan, Jacqueline Gottlieb, Massimo Silvetti","doi":"10.1017/S0140525X24000219","DOIUrl":"https://doi.org/10.1017/S0140525X24000219","url":null,"abstract":"<p><p>We argue that the type of meta-learning proposed by Binz et al. generates models with low interpretability and falsifiability that have limited usefulness for neuroscience research. An alternative approach to meta-learning based on hyperparameter optimization obviates these concerns and can generate empirically testable hypotheses of biological computations.</p>","PeriodicalId":8698,"journal":{"name":"Behavioral and Brain Sciences","volume":null,"pages":null},"PeriodicalIF":16.6,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142279939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Bayes beyond the predictive distribution. 贝叶斯超越了预测分布。
IF 16.6 1区 心理学
Behavioral and Brain Sciences Pub Date : 2024-09-23 DOI: 10.1017/S0140525X24000086
Anna Székely, Gergő Orbán
{"title":"Bayes beyond the predictive distribution.","authors":"Anna Székely, Gergő Orbán","doi":"10.1017/S0140525X24000086","DOIUrl":"https://doi.org/10.1017/S0140525X24000086","url":null,"abstract":"<p><p>Binz et al. argue that meta-learned models offer a new paradigm to study human cognition. Meta-learned models are proposed as alternatives to Bayesian models based on their capability to learn identical posterior predictive distributions. In our commentary, we highlight several arguments that reach beyond a predictive distribution-based comparison, offering new perspectives to evaluate the advantages of these modeling paradigms.</p>","PeriodicalId":8698,"journal":{"name":"Behavioral and Brain Sciences","volume":null,"pages":null},"PeriodicalIF":16.6,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142279917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Meta-learned models as tools to test theories of cognitive development. 将元学习模型作为检验认知发展理论的工具。
IF 16.6 1区 心理学
Behavioral and Brain Sciences Pub Date : 2024-09-23 DOI: 10.1017/S0140525X24000281
Kate Nussenbaum, Catherine A Hartley
{"title":"Meta-learned models as tools to test theories of cognitive development.","authors":"Kate Nussenbaum, Catherine A Hartley","doi":"10.1017/S0140525X24000281","DOIUrl":"https://doi.org/10.1017/S0140525X24000281","url":null,"abstract":"<p><p>Binz et al. argue that meta-learned models are essential tools for understanding adult cognition. Here, we propose that these models are particularly useful for testing hypotheses about why learning processes change across development. By leveraging their ability to discover optimal algorithms and account for capacity limitations, researchers can use these models to test competing theories of developmental change in learning.</p>","PeriodicalId":8698,"journal":{"name":"Behavioral and Brain Sciences","volume":null,"pages":null},"PeriodicalIF":16.6,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142279924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Challenges of meta-learning and rational analysis in large worlds. 大型世界中元学习和理性分析的挑战。
IF 16.6 1区 心理学
Behavioral and Brain Sciences Pub Date : 2024-09-23 DOI: 10.1017/S0140525X24000128
Margherita Calderan, Antonino Visalli
{"title":"Challenges of meta-learning and rational analysis in large worlds.","authors":"Margherita Calderan, Antonino Visalli","doi":"10.1017/S0140525X24000128","DOIUrl":"https://doi.org/10.1017/S0140525X24000128","url":null,"abstract":"<p><p>We challenge Binz et al.'s claim of meta-learned model superiority over Bayesian inference for large world problems. While comparing Bayesian priors to model-training decisions, we question meta-learning feature exclusivity. We assert no special justification for rational Bayesian solutions to large world problems, advocating exploring diverse theoretical frameworks beyond rational analysis of cognition for research advancement.</p>","PeriodicalId":8698,"journal":{"name":"Behavioral and Brain Sciences","volume":null,"pages":null},"PeriodicalIF":16.6,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142279918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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