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Hsu, Anne S.; Horng, Andy; Griffiths, Thomas L.; Chater, Nick – Cognitive Science, 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…
Descriptors: Statistical Inference, Bayesian Statistics, Evidence, Prediction
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Lee, Hee Seung; Betts, Shawn; Anderson, John R. – Cognitive Science, 2016
Learning to solve a class of problems can be characterized as a search through a space of hypotheses about the rules for solving these problems. A series of four experiments studied how different learning conditions affected the search among hypotheses about the solution rule for a simple computational problem. Experiment 1 showed that a problem…
Descriptors: Problem Solving, Hypothesis Testing, Experiments, Cognitive Processes
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Janssen, Christian P.; Gray, Wayne D. – Cognitive Science, 2012
Reinforcement learning approaches to cognitive modeling represent task acquisition as learning to choose the sequence of steps that accomplishes the task while maximizing a reward. However, an apparently unrecognized problem for modelers is choosing when, what, and how much to reward; that is, when (the moment: end of trial, subtask, or some other…
Descriptors: Rewards, Reinforcement, Models, Memory
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Hawkins, Guy; Brown, Scott D.; Steyvers, Mark; Wagenmakers, Eric-Jan – Cognitive Science, 2012
For decisions between many alternatives, the benchmark result is Hick's Law: that response time increases log-linearly with the number of choice alternatives. Even when Hick's Law is observed for response times, divergent results have been observed for error rates--sometimes error rates increase with the number of choice alternatives, and…
Descriptors: Bayesian Statistics, Reaction Time, Context Effect, Decision Making
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Griffiths, Thomas L.; Christian, Brian R.; Kalish, Michael L. – Cognitive Science, 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…
Descriptors: Logical Thinking, Bias, Identification, Research Methodology
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Tentori, Katya; Bonini, Nicolao; Osherson, Daniel – Cognitive Science, 2004
It is easy to construct pairs of sentences X, Y that lead many people to ascribe higher probability to the conjunction X-and-Y than to the conjuncts X, Y. Whether an error is thereby committed depends on reasoners' interpretation of the expressions "probability" and "and." We report two experiments designed to clarify the normative status of…
Descriptors: Form Classes (Languages), Experiments, Responses, Pragmatics