Concepts
Nov 18, 2019
Understanding human conceptual knowledge is one of the central problems in cognitive science. I focus on a number of key questions. How is knowledge organised in the mind? How do the assumptions people make about how data is generated, especially the social assumptions about the motivations of the providers, drive their conceptual knowledge and what they do with it? What kind of inductive inferences are licensed by our conceptual knowledge, and what are not? What must be “built in” in order to explain human category learning?
Current projects involve understanding how people learn complex categories, what kind of conceptual inferences people make based on different types of statistical sampling, and how concepts (especially social concepts) change and why. I also study concepts and meaning by looking how words are connected in our mental dictionary. Besides this, previous work (to which I may return) focuses on the role of labels in concept learning and learning categories with different kinds of structure.
Andrew Perfors
Professor
I seek to understand how people reason and think, both on their own and in groups.
Publications
Simon De Deyne, Sophie Warner, Andrew Perfors
(2023).
Common words, uncommon meanings: Evidence for widespread gender differences in word meaning.
In M Goldwater and F Anggoro and B Hayes and D Ong (Eds.) Proceedings of the 45th Annual Conference of the Cognitive Science Society: Manuscript under review.
Manikya Alister, Keith Ransom, Andrew Perfors
(2023).
Inferring the truth from deception: What can people learn from helpful and unhelpful information providers?.
In M Goldwater and F Anggoro and B Hayes and D Ong (Eds.) Proceedings of the 45th Annual Conference of the Cognitive Science Society: Manuscript under review.
Jessica Marris, Andrew Perfors, Robert Gibson, Frank Gaillard, Piers Howe
(2023).
Testing the effectiveness of augmenting perceptual training with annotations and steps in a difficult visual discrimination task.
In M Goldwater and F Anggoro and B Hayes and D Ong (Eds.) Proceedings of the 45th Annual Conference of the Cognitive Science Society: Manuscript under review.
Jessica Marris, Andrew Perfors, David Mitchell, Wayland Wang, Mark McCusker, Timothy Lovell, Robert Gibson, Frank Gaillard, Piers Howe
(2023).
Evaluating the effectiveness of different perceptual training methods in a difficult visual discrimination task with ultrasound images.
Cognitive Research: Principles and Implications.
Keith Ransom, Andrew Perfors, Brett Hayes, Saoirse Connor Desai
(2022).
What do our sampling assumptions affect: How we encode data or how we reason from it?.
Journal of Experimental Psychology: Learning, Memory, and Cognition.
Andrew Wang, Simon De Deyne, Meredith McKague, Andrew Perfors
(2022).
Core words in semantic representation.
In J Culbertson and A Perfors and H Rabagliati and V Ramenzoni (Eds.) Proceedings of the 44th Annual Conference of the Cognitive Science Society: 962-968.
Jerome Han, Keith Ransom, Andrew Perfors, Charles Kemp
(2022).
Human-like property induction is a challenge for large language models.
In J Culbertson and A Perfors and H Rabagliati and V Ramenzoni (Eds.) Proceedings of the 44th Annual Conference of the Cognitive Science Society: 2782-2788.
Manikya Alister, Keith Ransom, Andrew Perfors
(2022).
Source independence affects argument persuasiveness when the relevance is clear.
In J Culbertson and A Perfors and H Rabagliati and V Ramenzoni (Eds.) Proceedings of the 44th Annual Conference of the Cognitive Science Society: 2767-2773.
Jessica Sullivan, Michelle Mei, Andrew Perfors, Erica Wojcik, Michael Frank
(2021).
A large, longitudinal audiovisual dataset recorded from the infant’s perspective.
Open Mind 5: 20-29.
Jessica Marris, Andrew Perfors, David Mitchell, Wayland Wang, Mark McCusker, Timothy Lovell, Robert Gibson, Frank Gaillard, Piers Howe
(2021).
How effective is perceptual training? Evaluating two perceptual training methods on a difficult visual categorisation task.
In T Fitch and C Lamm and H Leder and K Tessmar-Raible (Eds.) Proceedings of the 43rd Annual Conference of the Cognitive Science Society: 2678-2684.
Keith Ransom, Andrew Perfors, Rachel Stephens
(2021).
Social meta-inference and the evidentiary value of consensus.
In T Fitch and C Lamm and H Leder and K Tessmar-Raible (Eds.) Proceedings of the 43rd Annual Conference of the Cognitive Science Society: 833-839.
Simon De Deyne, Danielle Navarro, Guillem Collell, Andrew Perfors
(2021).
Visual and affective multimodal models of word meaning in language and mind.
Cognitive Science 45(1): e12922.
Keith Ransom, Wouter Voorspoels, Danielle Navarro, Andrew Perfors
(2019).
Where the truth lies: How sampling implications drive deception without lying.
Manuscript.
Simon De Deyne, Danielle Navarro, Andrew Perfors, Marc Brysbaert, Gert Storms
(2019).
The "Small World of Words" English word association norms for over 12,000 cue words.
Behaviour Research Methods 51: 987-1006 [Best paper of the year].
Keith Ransom, Andrew Perfors
(2019).
Exploring the role that encoding and retrieval play in sampling effects.
In A Goel, C Seifert, and C Freksa (Eds.) Proceedings of the 41st Annual Conference of the Cognitive Science Society: 946-952.
Wai Keen Vong, Andrew Hendrickson, Danielle Navarro, Andrew Perfors
(2019).
Do additional features help or hurt category learning? The curse of dimensionality in human learners.
Cognitive Science 43.
Andrew Hendrickson, Andrew Perfors, Danielle Navarro, Keith Ransom
(2019).
Sample size, number of categories and sampling assumptions: Exploring some differences between categorization and generalization.
Cognitive Psychology 111: 80-102.
Keith Ransom, Wouter Voorspoels, Andrew Perfors, Danielle Navarro
(2017).
A cognitive analysis of deception without lying.
In G Gunzelmann, A Howes, T Tenbrink, and E Davelaar (Eds.) Proceedings of the 39th Annual Conference of the Cognitive Science Society: 992-997.
Steven Langsford, Andrew Hendrickson, Andrew Perfors, Danielle Navarro
(2017).
When do learned transformations influence similarity and categorization?.
In G Gunzelmann, A Howes, T Tenbrink, and E Davelaar (Eds.) Proceedings of the 39th Annual Conference of the Cognitive Science Society: 2530-2535.
Dinis Gokaydin, Danielle Navarro, Anna Ma-Wyatt, Andrew Perfors
(2016).
The structure of sequential effects.
Journal of Experimental Psychology: General 145: 110-123.
Simon De Deyne, Andrew Perfors, Danielle Navarro
(2016).
Predicting human similarity judgments with distributional models: The value of word associations.
26th International Conference on Computational Linguistics, Osaka, Japan: 1861-1870. [Best Paper Award].
Keith Ransom, Andrew Perfors, Danielle Navarro
(2016).
Leaping to conclusions: Why premise relevance affects argument strength.
Cognitive Science 40(7): 1775-1796.
Wai Keen Vong, Danielle Navarro, Andrew Perfors
(2016).
The helpfulness of category labels in semi-supervised learning depends on category structure.
Psychonomic Bulletin and Review, 23: 230-238.
Wai Keen Vong, Andrew Hendrickson, Andrew Perfors, Danielle Navarro
(2016).
Do additional features help or harm during category learning? An exploration of the curse of dimensionality in human learners.
In A Papafragou, D Grodner, D Mirman and JC Trueswell (Eds.) Proceedings of the 38th Annual Conference of the Cognitive Science Society: 2471-2476. [Marr Prize Winner].
Simon De Deyne, Danielle Navarro, Andrew Perfors, Gert Storms
(2016).
Structure at every scale: A semantic network account of the similarities between very unrelated concepts.
Journal of Experimental Psychology: General, 145(9): 1228-1254.
Wouter Voorspoels, Danielle Navarro, Andrew Perfors, Keith Ransom, Gert Storms
(2015).
How do people learn from negative evidence? Non-monotonic generalizations and sampling assumptions in inductive reasoning.
Cognitive Psychology 81: 1-25.
Steven Langsford, Andrew Hendrickson, Andrew Perfors, Danielle Navarro
(2014).
People are sensitive to hypothesis sparsity during category discrimination.
In P Bellow, M Guarani, M McShane and B Scassellati (Eds.) Proceedings of the 36th Annual Conference of the Cognitive Science Society: 2531-2536.
Andrew Perfors, Keith Ransom, Danielle Navarro
(2014).
People ignore token frequency when deciding how widely to generalize.
In P Bellow, M Guarani, M McShane and B Scassellati (Eds.) Proceedings of the 36th Annual Conference of the Cognitive Science Society: 2759-2764.
Wai Keen Vong, Andrew Perfors, Danielle Navarro
(2014).
The relevance of labels in semi-supervised learning depends on category structure.
In P Bellow, M Guarani, M McShane and B Scassellati (Eds.) Proceedings of the 36th Annual Conference of the Cognitive Science Society: 1718-1723.
Wai Keen Vong, Andrew Hendrickson, Andrew Perfors, Danielle Navarro
(2013).
The role of sampling assumptions in generalization with multiple categories.
In M Knauff, M Pauen, N Sebanz and I Wachsmuth (Eds.) Proceedings of the 35th Annual Conference of the Cognitive Science Society: 3699-3704.
Danielle Navarro, Andrew Perfors
(2012).
Anticipating changes: Adaptation and extrapolation in category learning.
In N Miyake, D Peebles and RP Cooper (Eds.) Proceedings of the 34th Annual Conference of the Cognitive Science Society: 809-814.
Simon De Deyne, Danielle Navarro, Andrew Perfors, Gert Storms
(2012).
Strong structure in weak semantic similarity: A graph based account.
In N Miyake, D Peebles and RP Cooper (Eds.) Proceedings of the 34th Annual Conference of the Cognitive Science Society: 1464-1469.
Patrick Shafto, Baxter Eaves, Danielle Navarro, Andrew Perfors
(2012).
Epistemic trust: Modeling children's reasoning about others' knowledge and intent.
Developmental Science 15: 436-447.
Dinis Gokaydin, Anna Ma-Wyatt, Danielle Navarro, Andrew Perfors
(2011).
Humans use different statistics for sequence analysis depending on the task.
In L Carlson (Ed.) Proceedings of the 33rd Annual Conference of the Cognitive Science Society: 543-548.
Robert Montague, Danielle Navarro, Andrew Perfors, Russell Warner, Patrick Shafto
(2011).
To catch a liar: The effects of truthful and deceptive testimony on inferential learning.
In L Carlson (Ed.) Proceedings of the 33rd Annual Conference of the Cognitive Science Society: 1312-1317.
Danielle Navarro, Andrew Perfors
(2010).
Similarity, feature discovery, and the size principle.
Acta Psychologica 133: 256-268.
Danielle Navarro, Andrew Perfors
(2009).
Learning time-varying categories.
N Taatgen, H Rijn, L Schomaker and J Nerbonne (Eds.) Proceedings of the 31st Annual Meeting of the Cognitive Science Society: 419-424.
Andrew Perfors, Josh Tenenbaum
(2009).
Learning to learn categories.
N Taatgen, H Rijn, L Schomaker and J Nerbonne (Eds.) Proceedings of the 31st Annual Meeting of the Cognitive Science Society: 136-141.
Fei Xu, Kathryn Dewar, Andrew Perfors
(2009).
Induction, overhypotheses, and the shape bias: Some arguments and evidence for rational constructivism.
In B Hood and L Santos (Eds.) The origins of object knowledge: 263-284.
Andrew Perfors
(2008).
Learnability, representation, and language: A Bayesian approach.
PhD Thesis. Massachusetts Institute of Technology Department of Brain and Cognitive Sciences. Cambridge, MA.
Charles Kemp, Andrew Perfors, Josh Tenenbaum
(2007).
Learning overhypotheses with hierarchical Bayesian models.
Developmental Science 10: 307-321.
Charles Kemp, Andrew Perfors, Josh Tenenbaum
(2006).
Learning overhypotheses.
In R Sun and N Miyake (Eds.) Proceedings of the 28th Annual Conference of the Cognitive Science Society: 417-422.
Andrew Perfors, Charles Kemp, Josh Tenenbaum
(2005).
Modeling the acquisition of domain structure and feature understanding.
In B Bara, L Barsalou and M Bucciarelli (Eds.) Proceedings of the 27th Annual Conference of the Cognitive Science Society: 1720-1725.
Charles Kemp, Andrew Perfors, Josh Tenenbaum
(2004).
Learning domain structures.
In K Forbus, D Gentner and T Regier. (Eds.) Proceedings of the 26th Annual Conference of the Cognitive Science Society: 672-677.