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Kocab, Annemarie; Davidson, Kathryn; Snedeker, Jesse – Cognitive Science, 2022
Classical quantifiers (like "all," "some," and "none") express relationships between two sets, allowing us to make generalizations (like "no elephants fly"). Devices like these appear to be universal in human languages. Is the ubiquity of quantification due to a universal property of the human mind or is it…
Descriptors: Natural Language Processing, Form Classes (Languages), Cognitive Processes, Spanish
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Richie, Russell; Bhatia, Sudeep – Cognitive Science, 2021
Similarity is one of the most important relations humans perceive, arguably subserving category learning and categorization, generalization and discrimination, judgment and decision making, and other cognitive functions. Researchers have proposed a wide range of representations and metrics that could be at play in similarity judgment, yet have not…
Descriptors: Classification, Generalization, Decision Making, Cognitive Processes
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Hannagan, Thomas; Grainger, Jonathan – Cognitive Science, 2012
It has been recently argued that some machine learning techniques known as Kernel methods could be relevant for capturing cognitive and neural mechanisms (Jakel, Scholkopf, & Wichmann, 2009). We point out that "String kernels," initially designed for protein function prediction and spam detection, are virtually identical to one contending proposal…
Descriptors: Brain, Word Recognition, Visual Discrimination, Orthographic Symbols
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Ritter, Frank E.; Bibby, Peter A. – Cognitive Science, 2008
We have developed a process model that learns in multiple ways while finding faults in a simple control panel device. The model predicts human participants' learning through its own learning. The model's performance was systematically compared to human learning data, including the time course and specific sequence of learned behaviors. These…
Descriptors: Problem Solving, Artificial Intelligence, Comparative Analysis, Task Analysis