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18Parallelograms revisited: Exploring the limitations of vector space models for simple analogiesCognition 205 (C): 104440. 2020.
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10Reconciling novelty and complexity through a rational analysis of curiosityPsychological Review 127 (3): 455-476. 2020.
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16Learning How to GeneralizeCognitive Science 43 (8). 2019.Generalization is a fundamental problem solved by every cognitive system in essentially every domain. Although it is known that how people generalize varies in complex ways depending on the context or domain, it is an open question how people learn the appropriate way to generalize for a new context. To understand this capability, we cast the problem of learning how to generalize as a problem of learning the appropriate hypothesis space for generalization. We propose a normative mathematical fra…Read more
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33Using Category Structures to Test Iterated Learning as a Method for Identifying Inductive BiasesCognitive Science 32 (1): 68-107. 2008.Many of the problems studied in cognitive science are inductive problems, requiring people to evaluate hypotheses in the light of data. The key to solving these problems successfully is having the right inductive biases—assumptions about the world that make it possible to choose between hypotheses that are equally consistent with the observed data. This article explores a novel experimental method for identifying the biases that guide human inductive inferences. The idea behind this method is si…Read more
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67Evaluating (and Improving) the Correspondence Between Deep Neural Networks and Human RepresentationsCognitive Science 42 (8): 2648-2669. 2018.Decades of psychological research have been aimed at modeling how people learn features and categories. The empirical validation of these theories is often based on artificial stimuli with simple representations. Recently, deep neural networks have reached or surpassed human accuracy on tasks such as identifying objects in natural images. These networks learn representations of real‐world stimuli that can potentially be leveraged to capture psychological representations. We find that state‐of‐th…Read more
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10© 2017 Psychonomic Society, Inc.Cognitive biases, such as the anchoring bias, pose a serious challenge to rational accounts of human cognition. We investigate whether rational theories can meet this challenge by taking into account the mind’s bounded cognitive resources. We asked what reasoning under uncertainty would look like if people made rational use of their finite time and limited cognitive resources. To answer this question, we applied a mathematical theory of bounded rationality to the …Read more
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19A role for the developing lexicon in phonetic category acquisitionPsychological Review 120 (4): 751-778. 2013.
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36The influence of categories on perception: Explaining the perceptual magnet effect as optimal statistical inferencePsychological Review 116 (4): 752-782. 2009.
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4Education in/for Socialism: Historical, Current and Future Perspectives (edited book)Routledge. 2015.This book re-examines aspects of historical socialism, and includes case studies of education within twenty-first century socialist and post-socialist contexts shaped by the trajectories of historical socialism. Through these case studies, contributions offer insights into key questions: How are education systems and student subjectivities shaped by post-socialist trajectories and current regional politics, economics and resistance movements? How do sedimented socialist discourses and geographie…Read more
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21Immanuel Wallerstein and István Mészáros are prolific scholars whose analyses of global capitalism in crisis offer distinctive insight for research across the social sciences. This book engages readers with their main theses, encouraging the application of these in our analysis of social reality and as its mass educational institutions. Griffiths and Imre undertake this task in their presentation of work under the capitalist world-economy, and the official function of mass education to prepare w…Read more
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31Inferring Learners' Knowledge From Their ActionsCognitive Science 39 (3): 584-618. 2015.Watching another person take actions to complete a goal and making inferences about that person's knowledge is a relatively natural task for people. This ability can be especially important in educational settings, where the inferences can be used for assessment, diagnosing misconceptions, and providing informative feedback. In this paper, we develop a general framework for automatically making such inferences based on observed actions; this framework is particularly relevant for inferring stude…Read more
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27Compositionality in rational analysis: Grammar-based induction for concept learningIn Nick Chater & Mike Oaksford (eds.), The Probabilistic Mind: Prospects for Bayesian Cognitive Science, Oxford University Press. 2008.
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19Rational analysis as a link between human memory and information retrievalIn Nick Chater & Mike Oaksford (eds.), The Probabilistic Mind: Prospects for Bayesian Cognitive Science, Oxford University Press. pp. 329--349. 2008.
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31Learning hypothesis spaces and dimensions through concept learningIn S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society, Cognitive Science Society. pp. 73--78. 2010.
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33Learning from actions and their consequences: Inferring causal variables from continuous sequences of human actionIn N. A. Taatgen & H. van Rijn (eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society, . pp. 134. 2009.
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29Replicating color term universals through human iterated learningIn S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society, Cognitive Science Society. 2010.
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12Learning phonetic categories by learning a lexiconIn N. A. Taatgen & H. van Rijn (eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society, . 2009.
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19A formal analysis of cultural evolution by replacementIn B. C. Love, K. McRae & V. M. Sloutsky (eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society, Cognitive Science Society. pp. 1435--1400. 2008.
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333A tutorial introduction to Bayesian models of cognitive developmentCognition 120 (3): 302-321. 2011.
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Aarhus UniversityGraduate student
Areas of Specialization
Philosophy of Mind |
Philosophy of Cognitive Science |
Areas of Interest
Philosophy of Mind |
Philosophy of Cognitive Science |