The scientist’s investigation covers issues in Artificial intelligence, Cognitive science, Cognitive architecture, Inference and Connectionism. As part of his studies on Artificial intelligence, John E. Hummel often connects relevant subjects like Pattern recognition. His Pattern recognition research includes elements of Object, Cognitive neuroscience of visual object recognition, Binding problem and Communication.
His work deals with themes such as Cognitive psychology, Invariant, Perception and Priming, which intersect with Cognitive neuroscience of visual object recognition. His work carried out in the field of Cognitive architecture brings together such families of science as Schema, Analogy, Artificial neural network and Generalization. His studies in Analogy integrate themes in fields like Relational complexity and Relational integration.
John E. Hummel mainly focuses on Artificial intelligence, Cognitive science, Cognitive psychology, Cognition and Analogy. The concepts of his Artificial intelligence study are interwoven with issues in Natural language processing, Computer vision and Pattern recognition. His Cognitive science study incorporates themes from Schema, Mental representation, Cognitive architecture and Connectionism.
His Cognitive psychology study combines topics in areas such as Cognitive neuroscience of visual object recognition, Social psychology, Invariant and Categorization. He interconnects Perception and Computational model in the investigation of issues within Cognition. He has included themes like Theoretical computer science, Inference, Representation and Logical reasoning in his Analogy study.
John E. Hummel mostly deals with Artificial intelligence, Cognitive psychology, Cognitive science, Set and Cognitive neuroscience of visual object recognition. His Artificial intelligence research includes themes of Cognitive development, Encoding, Natural language processing, Relation and Analogy. His Analogy course of study focuses on Cognition and Spatial relation and Communication.
John E. Hummel combines subjects such as Object and Family resemblance with his study of Cognitive psychology. His Cognitive science study combines topics from a wide range of disciplines, such as Code, Theoretical computer science, Connectionism and Mathematical logic. His biological study deals with issues like Artificial neural network, which deal with fields such as Metric and Representation.
John E. Hummel mainly focuses on Cognitive psychology, Cognition, Analogy, Cognitive science and Artificial intelligence. His Cognitive psychology study integrates concerns from other disciplines, such as Object, Working memory and Communication. His biological study spans a wide range of topics, including Spatial relation, Perception, Multiplicative function, Acceleration and Relation.
His Analogy research incorporates elements of Irrational number, Semantic reasoner, Inference and Mathematical logic. As part of his studies on Cognitive science, he often connects relevant areas like Animal cognition. John E. Hummel studies Artificial intelligence, focusing on Disjunction elimination in particular.
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Distributed representations of structure: A theory of analogical access and mapping.
John E. Hummel;Keith J. Holyoak.
Psychological Review (1997)
Dynamic binding in a neural network for shape recognition.
John E. Hummel;Irving Biederman.
Psychological Review (1992)
A symbolic-connectionist theory of relational inference and generalization.
John E. Hummel;Keith J. Holyoak.
Psychological Review (2003)
A Theory of the Discovery and Predication of Relational Concepts.
Leonidas A. A. Doumas;John E. Hummel;Catherine M. Sandhofer.
conference cognitive science (2008)
Countering antivaccination attitudes
Zachary Horne;Derek Powell;John E. Hummel;Keith J. Holyoak.
Proceedings of the National Academy of Sciences of the United States of America (2015)
A Neurocomputational Model of Analogical Reasoning and its Breakdown in Frontotemporal Lobar Degeneration
Robert G. Morrison;Daniel C. Krawczyk;Keith J. Holyoak;John E. Hummel.
Journal of Cognitive Neuroscience (2004)
Relational integration, inhibition, and analogical reasoning in older adults.
Indre V. Viskontas;Robert G. Morrison;Keith J. Holyoak;John E. Hummel.
Psychology and Aging (2004)
Where View-based Theories Break Down: The Role of Structure in Shape Perception and Object Recognition
John E. Hummel.
Metric invariance in object recognition: a review and further evidence.
Eric E. Cooper;Irving Biederman;John E. Hummel.
Canadian Journal of Psychology/revue Canadienne De Psychologie (1992)
A neurocomputational system for relational reasoning
Barbara J. Knowlton;Robert G. Morrison;John E. Hummel;Keith J. Holyoak.
Trends in Cognitive Sciences (2012)
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