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3Replies to commentaries on beyond playing 20 questions with natureBehavioral and Brain Sciences 47. 2024.Commentaries on the target article offer diverse perspectives on integrative experiment design. Our responses engage three themes: (1) Disputes of our characterization of the problem, (2) skepticism toward our proposed solution, and (3) endorsement of the solution, with accompanying discussions of its implementation in existing work and its potential for other domains. Collectively, the commentaries enhance our confidence in the promise and viability of integrative experiment design, while highl…Read more
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17Beyond playing 20 questions with nature: Integrative experiment design in the social and behavioral sciencesBehavioral and Brain Sciences 47. 2024.The dominant paradigm of experiments in the social and behavioral sciences views an experiment as a test of a theory, where the theory is assumed to generalize beyond the experiment's specific conditions. According to this view, which Alan Newell once characterized as “playing twenty questions with nature,” theory is advanced one experiment at a time, and the integration of disparate findings is assumed to happen via the scientific publishing process. In this article, we argue that the process o…Read more
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8Optimal nudging for cognitively bounded agents: A framework for modeling, predicting, and controlling the effects of choice architecturesPsychological Review 130 (6): 1457-1491. 2023.
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5On the hazards of relating representations and inductive biasesBehavioral and Brain Sciences 46. 2023.The success of models of human behavior based on Bayesian inference over logical formulas or programs is taken as evidence that people employ a “language-of-thought” that has similarly discrete and compositional structure. We argue that this conclusion problematically crosses levels of analysis, identifying representations at the algorithmic level based on inductive biases at the computational level.
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10How do Humans Overcome Individual Computational Limitations by Working Together?Cognitive Science 47 (1). 2023.Since the cognitive revolution, psychologists have developed formal theories of cognition by thinking about the mind as a computer. However, this metaphor is typically applied to individual minds. Humans rarely think alone; compared to other animals, humans are curiously dependent on stores of culturally transmitted skills and knowledge, and we are particularly good at collaborating with others. Rather than picturing the human mind as an isolated computer, we can imagine each mind as a node in a…Read more
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8The Computational Challenges of Means Selection Problems: Network Structure of Goal Systems Predicts Human PerformanceCognitive Science 47 (8). 2023.We study human performance in two classical NP‐hard optimization problems: Set Cover and Maximum Coverage. We suggest that Set Cover and Max Coverage are related to means selection problems that arise in human problem‐solving and in pursuing multiple goals: The relationship between goals and means is expressed as a bipartite graph where edges between means and goals indicate which means can be used to achieve which goals. While these problems are believed to be computationally intractable in gen…Read more
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13Reconciling truthfulness and relevance as epistemic and decision-theoretic utilityPsychological Review 131 (1): 194-230. 2024.
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21Sensitivity to Shared Information in Social LearningCognitive Science 42 (1): 168-187. 2018.Social learning has been shown to be an evolutionarily adaptive strategy, but it can be implemented via many different cognitive mechanisms. The adaptive advantage of social learning depends crucially on the ability of each learner to obtain relevant and accurate information from informants. The source of informants’ knowledge is a particularly important cue for evaluating advice from multiple informants; if the informants share the source of their information or have obtained their information …Read more
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71One and Done? Optimal Decisions From Very Few SamplesCognitive Science 38 (4): 599-637. 2014.In many learning or inference tasks human behavior approximates that of a Bayesian ideal observer, suggesting that, at some level, cognition can be described as Bayesian inference. However, a number of findings have highlighted an intriguing mismatch between human behavior and standard assumptions about optimality: People often appear to make decisions based on just one or a few samples from the appropriate posterior probability distribution, rather than using the full distribution. Although sam…Read more
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17Reconciling intuitive physics and Newtonian mechanics for colliding objectsPsychological Review 120 (2): 411-437. 2013.
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47The evolution of frequency distributions: Relating regularization to inductive biases through iterated learningCognition 111 (3): 317-328. 2009.
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12Faster Teaching via POMDP PlanningCognitive Science 40 (6): 1290-1332. 2016.Human and automated tutors attempt to choose pedagogical activities that will maximize student learning, informed by their estimates of the student's current knowledge. There has been substantial research on tracking and modeling student learning, but significantly less attention on how to plan teaching actions and how the assumed student model impacts the resulting plans. We frame the problem of optimally selecting teaching actions using a decision-theoretic approach and show how to formulate t…Read more
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11Greater learnability is not sufficient to produce cultural universalsCognition 129 (1): 70-87. 2013.
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24Analyzing the Rate at Which Languages Lose the Influence of a Common AncestorCognitive Science 38 (7): 1406-1431. 2014.Analyzing the rate at which languages change can clarify whether similarities across languages are solely the result of cognitive biases or might be partially due to descent from a common ancestor. To demonstrate this approach, we use a simple model of language evolution to mathematically determine how long it should take for the distribution over languages to lose the influence of a common ancestor and converge to a form that is determined by constraints on language learning. We show that model…Read more
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7What the Baldwin Effect affects depends on the nature of plasticityCognition 197 (C): 104165. 2020.
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38The Wisdom of Individuals: Exploring People's Knowledge About Everyday Events Using Iterated LearningCognitive Science 33 (6): 969-998. 2009.Determining the knowledge that guides human judgments is fundamental to understanding how people reason, make decisions, and form predictions. We use an experimental procedure called ‘‘iterated learning,’’ in which the responses that people give on one trial are used to generate the data they see on the next, to pinpoint the knowledge that informs people's predictions about everyday events (e.g., predicting the total box office gross of a movie from its current take). In particular, we use this …Read more
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77Rational Use of Cognitive Resources: Levels of Analysis Between the Computational and the AlgorithmicTopics in Cognitive Science 7 (2): 217-229. 2015.Marr's levels of analysis—computational, algorithmic, and implementation—have served cognitive science well over the last 30 years. But the recent increase in the popularity of the computational level raises a new challenge: How do we begin to relate models at different levels of analysis? We propose that it is possible to define levels of analysis that lie between the computational and the algorithmic, providing a way to build a bridge between computational- and algorithmic-level models. The ke…Read more
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28Exploring Human Cognition Using Large Image DatabasesTopics in Cognitive Science 8 (3): 569-588. 2016.Most cognitive psychology experiments evaluate models of human cognition using a relatively small, well-controlled set of stimuli. This approach stands in contrast to current work in neuroscience, perception, and computer vision, which have begun to focus on using large databases of natural images. We argue that natural images provide a powerful tool for characterizing the statistical environment in which people operate, for better evaluating psychological theories, and for bringing the insights…Read more
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77Bayes and Blickets: Effects of Knowledge on Causal Induction in Children and AdultsCognitive Science 35 (8): 1407-1455. 2011.People are adept at inferring novel causal relations, even from only a few observations. Prior knowledge about the probability of encountering causal relations of various types and the nature of the mechanisms relating causes and effects plays a crucial role in these inferences. We test a formal account of how this knowledge can be used and acquired, based on analyzing causal induction as Bayesian inference. Five studies explored the predictions of this account with adults and 4-year-olds, using…Read more
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48Testing the Efficiency of Markov Chain Monte Carlo With People Using Facial Affect CategoriesCognitive Science 36 (1): 150-162. 2012.Exploring how people represent natural categories is a key step toward developing a better understanding of how people learn, form memories, and make decisions. Much research on categorization has focused on artificial categories that are created in the laboratory, since studying natural categories defined on high-dimensional stimuli such as images is methodologically challenging. Recent work has produced methods for identifying these representations from observed behavior, such as reverse corre…Read more
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61A Bayesian framework for word segmentation: Exploring the effects of contextCognition 112 (1): 21-54. 2009.
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41Learning the Form of Causal Relationships Using Hierarchical Bayesian ModelsCognitive Science 34 (1): 113-147. 2010.
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9How to Be Helpful to Multiple People at OnceCognitive Science 44 (6). 2020.When someone hosts a party, when governments choose an aid program, or when assistive robots decide what meal to serve to a family, decision‐makers must determine how to help even when their recipients have very different preferences. Which combination of people’s desires should a decision‐maker serve? To provide a potential answer, we turned to psychology: What do people think is best when multiple people have different utilities over options? We developed a quantitative model of what people co…Read more
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41Resource-rational analysis: understanding human cognition as the optimal use of limited computational resourcesBehavioral and Brain Sciences 1-85. forthcoming.
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40Word-level information influences phonetic learning in adults and infantsCognition 127 (3): 427-438. 2013.
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48When Absence of Evidence Is Evidence of Absence: Rational Inferences From Absent DataCognitive Science 41 (S5): 1155-1167. 2017.Identifying patterns in the world requires noticing not only unusual occurrences, but also unusual absences. We examined how people learn from absences, manipulating the extent to which an absence is expected. People can make two types of inferences from the absence of an event: either the event is possible but has not yet occurred, or the event never occurs. A rational analysis using Bayesian inference predicts that inferences from absent data should depend on how much the absence is expected t…Read more
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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 |