Michael L. Kalish

According to our database, Michael L. Kalish authored at least 14 papers between 2007 and 2025.

Collaborative distances:

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

2025

Classification Versus Observation through Within- and Between-Category Comparison.

Rachel Lynn Perri, Michael L. Kalish, Daniel Corral

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

Training Methods in Categorization: A Comparison of Classification and Observation on Rule Adoption and Rule Consistency.

Yu-Wei Chang, Michael L. Kalish, Daniel Corral

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

2024

Extending the Locally Bayesian Learning Model to Exemplar-Based Categorization with Continuous Features.

Yu-Wei Chang, Sinem Aytac, Cindy G. Mendoza Gonzalez, Michael L. Kalish, Daniel Corral

Proceedings of the 46th Annual Meeting of the Cognitive Science Society, 2024

Towards a Unified Model Describing Multiple Tasks: Extending the Retrieving Effectively from Memory Model to Categorization.

Sinem Aytac, Yu-Wei Chang, Michael L. Kalish, Daniel Corral

Proceedings of the 46th Annual Meeting of the Cognitive Science Society, 2024

2023

The Categorization Task is Insufficient to Distinguish between Strategies: A Case for Partial-XOR-like Tasks.

Yu-Wei Chang, Michael L. Kalish

Proceedings of the 45th Annual Meeting of the Cognitive Science Society, 2023

2015

A Bayesian Latent Mixture Approach to Modeling Individual Differences in Categorization Using General Recognition Theory.

Irina Danileiko, Michael D. Lee, Michael L. Kalish

Proceedings of the 37th Annual Meeting of the Cognitive Science Society, 2015

2013

The Effects of Cultural Transmission Are Modulated by the Amount of Information Transmitted.

Thomas L. Griffiths, Stephan Lewandowsky, Michael L. Kalish

Cogn. Sci., 2013

2011

Explaining How the Mind Works: On the Relation Between Cognitive Science and Philosophy.

Jonathan Trigg, Michael L. Kalish

Top. Cogn. Sci., 2011

Discovering Inductive Biases in Categorization through Iterated Learning.

Kevin Robert Canini, Thomas L. Griffiths, Wolf Vanpaemel, Michael L. Kalish

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

Grounding lexical choice in Bayesian inference.

Kyle Albarado, Michael L. Kalish

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

2009

The Wisdom of Individuals: Exploring People's Knowledge About Everyday Events Using Iterated Learning.

Stephan Lewandowsky, Thomas L. Griffiths, Michael L. Kalish

Cogn. Sci., 2009

2008

Using Category Structures to Test Iterated Learning as a Method for Identifying Inductive Biases.

Thomas L. Griffiths, Brian R. Christian, Michael L. Kalish

Cogn. Sci., 2008

Modeling human function learning with Gaussian processes.

Thomas L. Griffiths, Christopher G. Lucas, Joseph Jay Williams, Michael L. Kalish

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2007

Language Evolution by Iterated Learning With Bayesian Agents.

Thomas L. Griffiths, Michael L. Kalish

Cogn. Sci., 2007