A. Perfors

发表

How recursive is language? A Bayesian exploration

Joshua B. Tenenbaum, Amy Perfors, Edward Gibson, 2010 .

Probabilistic models of cognition: exploring representations and inductive biases

J. Tenenbaum, T. Griffiths, Charles Kemp, 2010, Trends in Cognitive Sciences.

The impact of frequency on the evolution of category systems

Charles Kemp, Amy Perfors, Vanessa Ferdinand, 2019, CogSci.

Regularization or lexical probability-matching? How German speakers generalize plural morphology

H. Rabagliati, Kate McCurdy, A. Perfors, 2022, CogSci.

The learnability of abstract syntactic principles

J. Tenenbaum, Amy Perfors, T. Regier, 2011, Cognition.

Computational approaches to induction

Nick Chater, Amy Perfors, Alexander Clark, 2015 .

Learnability in practice

Nick Chater, Amy Perfors, Alexander Clark, 2015 .

Sensitivity to hypothesis size during information search.

Amy Perfors, Daniel J. Navarro, Andrew T. Hendrickson, 2016 .

When do memory limitations lead to regularization? An experimental and computational investigation

Amy Perfors, A. Perfors, 2012 .

Memory limitations alone do not lead to over-regularization: An experimental and computational investigation

Amy Perfors, A. Perfors, 2011, CogSci.

Adult language learners under cognitive load do not over-regularize like children

N. Burns, A. Perfors, 2010 .

Do Additional Features Help or Hurt Category Learning? The Curse of Dimensionality in Human Learners

Danielle J. Navarro, Amy Perfors, Andrew T. Hendrickson, 2018, Cogn. Sci..

Not every credible interval is credible: Evaluating robustness in the presence of contamination in Bayesian data analysis

Amy Perfors, Lauren A Kennedy, Daniel J Navarro, 2017, Behavior research methods.

Leaping to Conclusions: Why Premise Relevance Affects Argument Strength

Amy Perfors, Daniel J. Navarro, Keith Ransom, 2016, Cogn. Sci..

Bayesian Models of Cognition Revisited: Setting Optimality Aside and Letting Data Drive Psychological Theory

Amy Perfors, Mark Steyvers, Daniel J Navarro, 2017, Psychological review.

Bayesian Special Section Learning Overhypotheses with Hierarchical Bayesian Models

J. Tenenbaum, Charles Kemp, Amy Perfors, 2022 .

Bayesian Models of Cognition: What's Built in After All?

Amy Perfors, Amy Perfors, A. Perfors, 2012 .

People are sensitive to hypothesis sparsity during category discrimination

Amy Perfors, Daniel J. Navarro, Andrew Hendrickson, 2014, CogSci.

Hypothesis generation, sparse categories, and the positive test strategy.

Amy Perfors, D. Navarro, A. Perfors, 2011, Psychological review.

Learnability of syntax 1 Running head : LEARNABILITY OF SYNTAX The learnability of abstract syntactic principles

J. Tenenbaum, A. Perfors, 2008 .

Cross-situational learning in a Zipfian environment

Andrew T. Hendrickson, Amy Perfors, A. Perfors, 2018, Cognition.

The “Small World of Words” English word association norms for over 12,000 cue words

Amy Perfors, M. Brysbaert, D. Navarro, 2018, Behavior Research Methods.

Indirect Evidence and the Poverty of the Stimulus: The Case of Anaphoric One

Joshua B. Tenenbaum, Amy Perfors, Terry Regier, 2009, Cogn. Sci..

Evidence for widespread thematic structure in the mental lexicon

Amy Perfors, Daniel J. Navarro, Steven Verheyen, 2015, CogSci.

Learnability, representation, and language: a bayesian approach

Amy Perfors, A. Perfors, 2008 .

Poverty of the Stimulus? A Rational Approach

J. Tenenbaum, Amy Perfors, T. Regier, 2006 .

A tutorial introduction to Bayesian models of cognitive development

J. Tenenbaum, Fei Xu, T. Griffiths, 2011, Cognition.

Quantifying sentence acceptability measures : Reliability, bias, and variability

Amy Perfors, Andrew T. Hendrickson, Steven Langsford, 2018 .

Exploring the role that encoding and retrieval play in sampling effects

Amy Perfors, Keith Ransom, Keith Ransom, 2019, CogSci.

The Psychology of Cultural Dynamics: What Is It, What Do We Know, and What Is Yet to Be Known?

Amy Perfors, P. Bain, Y. Kashima, 2019, Annual review of psychology.

Adult Regularization of Inconsistent Input Depends on Pragmatic Factors

Amy Perfors, A. Perfors, 2016 .

Predicting human similarity judgments with distributional models: The value of word associations.

Amy Perfors, Daniel J. Navarro, Simon De Deyne, 2016, COLING.

Daniel J Navarro, Amy F Perfors, D. Navarro, 2010, Acta psychologica.

Sample size, number of categories and sampling assumptions: Exploring some differences between categorization and generalization

Danielle J. Navarro, Amy Perfors, Keith Ransom, 2019, Cognitive Psychology.

Structure at every scale: A semantic network account of the similarities between unrelated concepts.

Amy Perfors, Daniel J Navarro, Gert Storms, 2016, Journal of experimental psychology. General.

The “Small World of Words” English word association norms for over 12,000 cue words

M. Brysbaert, D. Navarro, G. Storms, 2018, Behavior Research Methods.

Picking up speed in understanding: Speech processing efficiency and vocabulary growth across the 2nd year.

Amy Perfors, Anne Fernald, Virginia A Marchman, 2006, Developmental psychology.

Efficiency in understanding 1 Picking Up Speed in Understanding : Speech Processing Efficiency and Vocabulary Growth Across the Second Year

Amy Perfors, Anne Fernald, Virginia A. Marchman, 2004 .

What do our sampling assumptions affect: How we encode data or how we reason from it?

Brett K. Hayes, Amy Perfors, Keith Ransom, 2021, Journal of experimental psychology. Learning, memory, and cognition.

Learning Overhypotheses

J. Tenenbaum, Charles Kemp, A. Perfors, 2006 .

Bayesian modeling of sources of constraint in language acquisition

Amy Perfors, Elizabeth Wonnacott, E. Wonnacott, 2011 .

Phonetic training makes word learning easier

Amy Perfors, D. Dunbar, A. Perfors, 2010 .

Amy Perfors: Simulated Evolution of Language

Amy Perfors, A. Perfors, 2008 .

Simulated Evolution of Language: a Review of the Field

Amy Perfors, A. Perfors, 2002, J. Artif. Soc. Soc. Simul..

Learning individual words and learning about words simultaneously

Joshua B. Tenenbaum, Fei Xu, Amy Perfors, 2011, CogSci.

Musicians are better at learning non-native sound contrasts even in non-tonal languages

Amy Perfors, Jia Hoong Ong, J. Ong, 2012, CogSci.

Do additional features help or harm during category learning? An exploration of the curse of dimensionality in human learners

Amy Perfors, Daniel J. Navarro, Wai Keen Vong, 2016, CogSci.

Language Evolution Can Be Shaped by the Structure of the World

Amy Perfors, Daniel J. Navarro, D. Navarro, 2014, Cogn. Sci..

What Bayesian modelling can tell us about statistical learning: What it requires and why it works

Amy Perfors, Daniel J. Navarro, D. Navarro, 2012 .

Language evolution is shaped by the structure of the world: An iterated learning analysis

Amy Perfors, Daniel J. Navarro, D. Navarro, 2011, CogSci.

Induction, overhypotheses, and the shape bias: Some arguments and evidence for rational constructivism

Fei Xu, Amy Perfors, K. Dewar, 2009 .

Learning to learn categories

J. Tenenbaum, Amy Perfors, A. Perfors, 2009 .

BAYESIAN SPECIAL SECTION Learning overhypotheses with hierarchical Bayesian models

J. Tenenbaum, Charles Kemp, Amy Perfors, 2007 .

Running head : LEARNING OVERHYPOTHESES Learning overhypotheses with hierarchical Bayesian models

Joshua B. Tenenbaum, Amy Perfors, Charles Kemp, 2006 .

Epistemic trust: modeling children's reasoning about others' knowledge and intent.

Baxter S. Eaves, Amy Perfors, Patrick Shafto, 2012, Developmental science.

The puzzle of ambiguity

David I. Beaver, Amy Perfors, T. Wasow, 2005 .

Visual and Affective Grounding in Language and Mind

Amy Perfors, Guillem Collell, Simon De Deyne, 2018 .

When Extremists Win: Cultural Transmission Via Iterated Learning When Populations Are Heterogeneous

Danielle J. Navarro, Amy Perfors, Scott D. Brown, 2018, Cogn. Sci..

When extremists win: On the behavior of iterated learning chains when priors are heterogeneous

Amy Perfors, Daniel J. Navarro, Scott Brown, 2017, CogSci.

Stronger evidence isn't always better: A role for social inference in evidence selection and interpretation

Patrick Shafto, Danielle J. Navarro, Amy Perfors, 2018, CogSci.

Why do echo chambers form? The role of trust, population heterogeneity, and objective truth

Danielle J. Navarro, Amy Perfors, D. Navarro, 2019, CogSci.

Variability, negative evidence, and the acquisition of verb argument constructions.

J. Tenenbaum, Amy Perfors, E. Wonnacott, 2010, Journal of child language.

Modeling the Acquisition of Domain Structure and Feature Understanding

J. Tenenbaum, Charles Kemp, Amy Perfors, 2005 .

The structure of sequential effects.

Amy Perfors, D. Navarro, Anna Ma-Wyatt, 2016, Journal of experimental psychology. General.

Reversing the endowment effect

P. Howe, Amy Perfors, Campbell Pryor, 2018, Judgment and Decision Making.

Levels of explanation and the workings of science

Amy Perfors, A. Perfors, 2012 .

Confirmation bias is rational when hypotheses are sparse

Amy Perfors, D. Navarro, A. Perfors, 2009 .

Generic noun phrases in child speech

Amy Perfors, Samarth Mehrotra, A. Perfors, 2019, CogSci.

How do people learn from negative evidence? Non-monotonic generalizations and sampling assumptions in inductive reasoning

Amy Perfors, D. Navarro, Wouter Voorspoels, 2015, Cognitive Psychology.

When to walk away: The effect of variability on keeping options viable

Anastasia Ejova, Amy Perfors, Daniel J. Navarro, 2009 .

The Exploration Advantage: Children’s instinct to explore allows them to find information that adults miss.

Amy Perfors, Emily Sumner, Barbara Wiseheart Sarnecka, 2019 .

Language learning, language use and the evolution of linguistic variation

Amy Perfors, Kenny Smith, Anna Samara, 2017, Philosophical Transactions of the Royal Society B: Biological Sciences.

REGULARIZATION OF LINGUISTIC VARIATION IN POPULATIONS

Amy Perfors, Kenny Smith, Elizabeth Wonnacott, 2012 .

Constraining generalisation in artificial language learning : children are rational too

Amy Perfors, Elizabeth Wonnacott, E. Wonnacott, 2009 .

Human decision making in black swan situations

Amy Perfors, Nicholas T. Van Dam, N. T. Dam, 2018, CogSci.

Where the truth lies: how sampling implications drive deception without lying

Amy Perfors, D. Navarro, Wouter Voorspoels, 2019 .

A cognitive analysis of deception without lying

Amy Perfors, Daniel J. Navarro, Keith Ransom, 2017, CogSci.

Humans use different statistics for sequence analysis depending on the task

Amy Perfors, Daniel J. Navarro, Anna Ma-Wyatt, 2011, CogSci.

Why are some word orders more common than others? A uniform information density account

Amy Perfors, Daniel J. Navarro, Luke Maurits, 2010, NIPS.

Running head: HOW RECURSIVE IS LANGUAGE

A. Perfors, 2008 .

Conformity to the descriptive norms of people with opposing political or social beliefs

P. Howe, Campbell Pryor, A. Perfors, 2019, PloS one.

Social meta-inference and the evidentiary value of consensus

Amy Perfors, Keith Ransom, Rachel G. Stephens, 2021, CogSci.

Piaget, Probability, Causality, and Contradiction

Amy Perfors, A. Perfors, 2016, Human Development.

Enlightenment grows from fundamentals

Amy Perfors, Daniel J. Navarro, D. Navarro, 2011, Behavioral and Brain Sciences.

Representational and sampling assumptions drive individual differences in single category generalisation

Danielle J. Navarro, Amy Perfors, Keith Ransom, 2018, CogSci.

People ignore token frequency when deciding how widely to generalize

Amy Perfors, Daniel J. Navarro, Keith Ransom, 2014, CogSci.

The role of sampling assumptions in generalization with multiple categories

Amy Perfors, Daniel J. Navarro, Wai Keen Vong, 2013, CogSci.

Even arbitrary norms influence moral decision-making

P. Howe, Campbell Pryor, A. Perfors, 2018, Nature Human Behaviour.

Strong structure in weak semantic similarity: A graph based account

Amy Perfors, Daniel J. Navarro, Gerrit Storms, 2012, CogSci.

Learning overhypotheses with hierarchical Bayesian models.

J. Tenenbaum, Charles Kemp, A. Perfors, 2007, Developmental science.

Even arbitrary norms influence moral decision-making

Amy Perfors, Piers D. L. Howe, Campbell Pryor, 2018, Nature Human Behaviour.

HETEROGENOUS ITERATED LEARNING 2

A. Perfors, Danielle J. Navarro, 2018 .

Probabilistic models of cognition: exploring representations and inductive biases

J. Tenenbaum, T. Griffiths, Charles Kemp, 2010, Trends in Cognitive Sciences.

Natively Probabilistic Computation by Vikash

Vikash K. Mansinghka, Keith Bonawitz, A. Perfors, 2009 .

Not every credible interval is credible: Evaluating robustness in the presence of contamination in Bayesian data analysis

D. Navarro, Nancy Briggs, A. Perfors, 2017, Behavior Research Methods.

Joint acquisition of word order and word reference

Amy Perfors, Luke Maurits, Daniel J. Navarro, 2009 .

Indirect Evidence and the Poverty of the Stimulus: The Case of Anaphoric One

J. Tenenbaum, T. Regier, Stephani Foraker, 2009, Cogn. Sci..

How does the presence of a label affect attention to other features

Amy Perfors, D. Navarro, A. Perfors, 2010 .

Social context effects on the impact of category labels

Rachel G. Stephens, Amy Perfors, D. Navarro, 2010 .

Variability, negative evidence, and the acquisition of verb argument constructions.

E. Wonnacott, A. Perfors, J. B. Tenenbaum, 2010, Journal of child language.

01. THE NAME OF THE AUTHOR(S) OF THE TARGET ARTICLE

Rolf A. Zwaan, P. Howe, B. Donnellan, 2018 .