John E. Hummel

According to our database, John E. Hummel authored at least 29 papers between 1993 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

From Basic Affordances to Symbolic Thought: A Computational Phylogenesis of Biological Intelligence.

John E. Hummel, Rachel F. Heaton

CoRR, August, 2025

Modeling the effect of cortical magnification on feature detection and individuation.

Rachel F. Heaton, John E. Hummel

Proceedings of the 47th Annual Meeting of the Cognitive Science Society, 2025

2024

MindSet: Vision. A toolbox for testing DNNs on key psychological experiments.

Valerio Biscione, Dong Yin, Gaurav Malhotra, Marin Dujmovic, Milton Llera Montero, Guillermo Puebla, Federico Adolfi, Rachel F. Heaton, John E. Hummel, Benjamin D. Evans, Karim Habashy, Jeffrey S. Bowers

CoRR, 2024

2023

On the importance of severely testing deep learning models of cognition.

Jeffrey S. Bowers, Gaurav Malhotra, Federico Adolfi, Marin Dujmovic, Milton Llera Montero, Valerio Biscione, Guillermo Puebla, John E. Hummel, Rachel F. Heaton

Cogn. Syst. Res., December, 2023

2022

Exaggeration of Stimulus Attributes in the Representation of Relational Categories.

Yuhui Du, John E. Hummel, Alexander A. Petrov

Proceedings of the 44th Annual Meeting of the Cognitive Science Society, 2022

2021

Probing the Mental Representation of Relation-Defined Categories.

Yuhui Du, John E. Hummel, Alexander A. Petrov

Proceedings of the 43rd Annual Meeting of the Cognitive Science Society, 2021

2020

Relation learning in a neurocomputational architecture supports cross-domain transfer.

Leonidas A. A. Doumas, Guillermo Puebla, Andrea E. Martin, John E. Hummel

Proceedings of the 42th Annual Meeting of the Cognitive Science Society, 2020

2019

Rapid Unsupervised Encoding of Object Files for Visual Reasoning.

Rachel F. Heaton, John E. Hummel

Proceedings of the 41th Annual Meeting of the Cognitive Science Society, 2019

2017

Do Machine-Learning Machines Learn?

Selmer Bringsjord, Naveen Sundar Govindarajulu, Shreya Banerjee, John E. Hummel

Proceedings of the Philosophy and Theory of Artificial Intelligence 2017, 2017

Automating the Encoding for the LISA Model of Analogy from Raw Text.

Sean Wilner, John E. Hummel

Proceedings of the 28th Modern Artificial Intelligence and Cognitive Science Conference 2017, 2017

2015

Making Probabilistic Relational Categories Learnable.

Wookyoung Jung, John E. Hummel

Cogn. Sci., 2015

A Single Counterexample Leads to Moral Belief Revision.

Zachary Horne, Derek Powell, John E. Hummel

Cogn. Sci., 2015

2013

The effects of dual verbal and visual tasks on featural vs. relational category learning.

Wookyoung Jung, John E. Hummel

Proceedings of the 35th Annual Meeting of the Cognitive Science Society, 2013

2012

Hierarchical Category Structures Facilitate Acquisition of Probabilistic Relational Categories.

Wookyoung Jung, John E. Hummel

Proceedings of the 34th Annual Meeting of the Cognitive Science Society, 2012

2011

Getting symbols out of a neural architecture.

John E. Hummel

Connect. Sci., 2011

Progressive Alignment Facilitates Learning of Deterministic But Not Probabilistic Relational Categories.

Wookyoung Jung, John E. Hummel

Proceedings of the 33th Annual Meeting of the Cognitive Science Society, 2011

Recognizing Geospatial Patterns with Biologically-inspired Relational Reasoning.

Paul Kogut, June Gordon, David Morgenthaler, John E. Hummel, Edward Monroe, Ben Goertzel, Ethan Trewhitt, Elizabeth T. Whitaker

Proceedings of the Biologically Inspired Cognitive Architectures 2011, 2011

Towards a Biologically-Inspired Model for Relational Mapping Using Spiking Neurons.

Paul Biancaniello, David Rosenbluth, Tom Szumowski, John Darvill, Nick Hinnerschitz, John E. Hummel, Stefan Mihalas

Proceedings of the Biologically Inspired Cognitive Architectures 2011, 2011

2010

Corrigendum to "Finding similarity in a model of relational reasoning" [Cognitive Systems Research 10 (2009) 229-239].

Eric G. Taylor, John E. Hummel

Cogn. Syst. Res., 2010

Symbolic Versus Associative Learning.

John E. Hummel

Cogn. Sci., 2010

A Computational Account of the Development of the Generalization of Shape Information.

Leonidas A. A. Doumas, John E. Hummel

Cogn. Sci., 2010

2009

Finding similarity in a model of relational reasoning.

Eric G. Taylor, John E. Hummel

Cogn. Syst. Res., 2009

Development of a Framework for Integrated Climate Impacts Analsese.

John Christiansen, John E. Hummel, Katherine Riley

Proceedings of the 2009 International Conference on Scientific Computing, 2009

2008

Toward a Process Model of Explanation with Implications for the Type-Token Problem.

John E. Hummel, David H. Landy, Derek Devnich

Proceedings of the Naturally-Inspired Artificial Intelligence, 2008

2005

The One-to-One Constraint in Analogical Mapping and Inference.

Daniel C. Krawczyk, Keith J. Holyoak, John E. Hummel

Cogn. Sci., 2005

2004

Varieties of sameness: the impact of relational complexity on perceptual comparisons.

James K. Kroger, Keith J. Holyoak, John E. Hummel

Cogn. Sci., 2004

A Solution to the Binding Problem for Compositional Connectionism.

John E. Hummel, Keith J. Holyoak, Collin B. Green, Leonidas A. A. Doumas, Derek Devnich, Aniket Kittur, Donald J. Kalar

Proceedings of the Compositional Connectionism in Cognitive Science, 2004

2003

"Effective systematicity" in, "effective systematicity" out: a reply to Edelman and Intrator (2003).

John E. Hummel

Cogn. Sci., 2003

1993

Geon Theory as an Account of Shape Recognition in Mind, Brain and Machine.

Irving Biederman, Eric Cooper, John E. Hummel, József Fiser

Proceedings of the British Machine Vision Conference, 1993