Canada

A milestone in cognitive development is understanding numerals to represent the exact number of discrete items in a set (i.e., the cardinal principle). This development has received much attention, but little is known about its relation to understanding numbers as measures of continuous quantity (e.g., “six blocks long” versus “six blocks”). To investigate this, 90 children were asked to complete two tasks: a give-a-number task, to assess cardinality knowledge, and a novel give-a-line task, to assess measurement knowledge. As expected, accuracy was greater on the give-a-number task than the give-a-line task. More unexpectedly, the quality of performance on the give-a-number task was as often negatively associated with quality of performance on the give-a-line task as it was positive correlated. Specifically, when asked to create a line N-blocks long, children who gave only approximately correct answers on the give-a-number task often outperformed children who gave exactly correct answers on the same task. These findings indicate that an approximate—and purportedly less mature—understanding of number possesses the hidden strength of being more flexible and suitable for measuring length.

CogSci 2022

Children’s Cardinality Knowledge Isn’t Always Beneficial

### Welcome to CogSci Conference 2025!

The 47th Annual Meeting of the Cognitive Science Society was a hybrid meeting held in San Francisco. 

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#### About

The Cognitive Science Society brings together researchers from around the world who hold a common goal: understanding the nature of the human mind. The mission of the Society is to promote Cognitive Science as a discipline, and to foster scientific interchange among researchers in various areas of study, including Artificial Intelligence, Linguistics, Anthropology, Psychology, Neuroscience, Philosophy, and Education.

The Society is a non-profit professional organization and its activities include sponsoring an annual conference and publishing the journals Cognitive Science and TopiCS.

#### Our History 

* **Society Creation**<br>
The Society was incorporated as a 501(c)(3) non-profit professional organization in Massachusetts in 1979. The organizing committee included Roger Schank, Allan Collins, Donald Norman, and a number of other scholars from psychology, linguistics, computer science, and philosophy. 
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* **Conference Creation**<br>
The first conference on cognitive science was held at La Jolla, California in August, 1979, and has occurred annually since then. The proceedings of each conference are published, and those from most years are available through Lawrence Erlbaum Associates, Inc. The annual proceedings of the Cognitive Science Conference represent a major source of information on new work and new ideas in the scientific study of thinking. In 1990, the Society, with help from an anonymous donor, established the David Marr Prize for the best student paper at each annual meeting.
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* **Journal Creation**<br>
The Journal, Cognitive Science, began publication in 1976, and is now published by Wiley-Blackwell. The Executive Editor is currently Richard P. Cooper of Birkbeck, University of London, and there are 18 Associate Editors and a 30-member editorial board. It serves as the premier outlet for research reports that intersect two or more disciplines. Copyrights for articles published in the journal are held by the Society. The Governing Board of the Cognitive Science Society voted in late 2006 to found a new journal, Topics in Cognitive Science (topiCS). The Editor in Chief is Wayne Gray, Cognitive Science Department, Rensselaer Polytechnic Institute. The journal seeks to fill a niche not occupied by Cognitive Science Journal or other cognitive science journals. Membership in the Society includes a subscription to Cognitive Science and TopiCS. Copyrights for articles published in the journal are held by the Society.
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CogSci 2025

The 47th Annual Meeting of the Cognitive Science Society presents the latest research across cognitive science and highlights the theme of Cognition in Context.

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Join us for CogSci2022! Our 44th Annual Conference will be centered around the theme of diversity, with an accompanying range of keynotes and invited speakers who themselves highlight the diversity of our field. Our three symposia are Cognition across Diverse Populations, Cognition within Diverse Societies, and Global Challenges for Cognitive Science. The conference is being offered in a fully hybrid environment for onsite and online attendees.
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The 44th Annual Meeting of the Cognitive Science Society highlighted research on the theme Cognitive Diversity in addition to the full breadth and diversity of research topics offered by the society’s membership. 





Dogs have a unique evolutionary relationship with humans and are relied upon in a variety of working roles, yet little is known about the kinds of visual information available to them, as well as how they direct their attention within their environment. The present study, inspired by comparable work in infants, aimed to categorize the visual statistics (specifically the identity of objects) available to dogs during a common event in their daily lives, a walk. Using a head-mounted eye-tracking apparatus that was custom designed for dogs, four dogs walked on a pre-determined route outdoors under naturalistic conditions generating a total of 49,431 frames for analysis. On average, there were few individual differences between dogs. Dogs looked proportionally more to people and plants than to other object categories in their environment, like the sky which they appeared to consider as background. The results of this project provide a foundational step towards understanding how dogs’ look at and interact with their physical world, opening up avenues for future research into how they complete tasks, and learn and make decisions, both independently and with a human social partner.

Categorizing Dogs’ Real World Visual Statistics

Central to rationality is the ability to think about our beliefs, and make sure they are based on good reasons. If we have several conflicting reasons to believe something, we wait for more information before making a decision, perhaps rechecking our original reasons before proceeding. In these studies, we presented great apes and young children with conflicting evidence about the location of a reward. We found that apes double-checked the evidence for their original choice before making a final decision, revealing an awareness of their own beliefs and reasoning not hitherto documented. Young children, in contrast, were more sensitive to peer disagreement than conflicting physical evidence, illustrating the distinctively social nature of human rationality.

Great Apes and Human Children Rationally Monitor their Decisions

From birth, humans constantly make decisions about what to look at and for how long. Yet the mechanism behind such decision-making remains poorly understood. Here we present the rational action, noisy choice for habituation (RANCH) model. RANCH is a rational learning model that takes noisy perceptual samples from stimuli and makes sampling decisions based on Expected Information Gain (EIG). The model captures key patterns of looking time documented in developmental research: habituation and dishabituation. We evaluated the model with adult looking time collected from a paradigm analogous to the infant habituation paradigm. We compared RANCH with baseline models (no learning model, no perceptual noise model) and models with alternative linking hypotheses (Surprisal, KL divergence). We showed that 1) learning and perceptual noise are critical assumptions of the model, and 2) Surprisal and KL are good proxies for EIG under the current learning context.

Habituation reflects optimal exploration over noisy perceptual samples

A central question in cognitive science is how semantic information is mentally represented. Two dominant theories of semantic representation are language-based distributional semantic models (which suggest that word meaning is based on which words co-occur in language) and semantic networks based on word associations (which suggest that words are represented as a network in which words with closer meanings are more closely linked). We investigate the issue of semantic representation through the lens of core vocabulary -- the set of words that are most central in the mental lexicon -- which these two theories make different predictions about. We report on the results of an experiment that tests which measure of core vocabulary most closely aligns with human behaviour in a word-guessing game where the aim was to identify a target word given a set of semantically related words as hints. Target and hint words, which varied across trials, were generated from different core vocabulary lists corresponding to these different theories. Results revealed that the type of hint words did not affect performance, but that better performance was attained for target words derived from word associations than from natural language distributional statistics. Follow-up analyses ruled out several alternate explanations. Our results suggest that the semantic information reflected in word associations may be more involved in the efficient identification of lexical meaning.

Core words in semantic representation

Can we know a word by the company it keeps? Aspects of meaning that concern physical interactions might be particularly difficult to learn from language alone. Glenberg & Robertson (2000) found that although human comprehenders were sensitive to the distinction between afforded and nonafforded actions, distributional semantic models were not. We tested whether technological advances have made distributional models more sensitive to affordances by replicating their experiment with modern Neural Language Models (NLMs). We found that only one NLM (GPT-3) was sensitive to the affordedness of actions. Moreover, GPT-3 accounted for only one third of the effect of affordedness on human sensibility judgments. These results imply that people use processes that go beyond distributional statistics to understand linguistic expressions, and that NLP systems may need to be augmented with such capabilities.

Distrubutional Semantics Still Can't Account for Affordances

Do people attribute functions to gendered social categories? (For instance, is there something men or mothers are for?) And if so, do such attributions of function have consequences for normative judgments about what members of these social categories ought to do? In the current study, participants (N = 366) rated their agreement with 15 statements about the “true functions” of different social categories, in triads of matched masculine, feminine, and superordinate categories (e.g., fathers, mothers, and parents). Participants endorsed functional claims more for some social categories (e.g., parents) than others (e.g., kids), and their background beliefs about gender predicted variation in functional reasoning. However, across categories, participants judged that fulfilling true functions was ‘natural’ for members of the category, and they judged that category members ought to fulfill their true functions.

What Are Men and Mothers For? The Causes and Consequences of Functional Reasoning About Social Categories

Word meanings extend over time due to a functional need for maintaining communicative expressivity within a compact lexicon. Previous scholars have suggested that word meanings extend via a process of chaining, whereby novel items link to existing ones close in semantic space. Recent work has formalized this idea using computational models grounded typically in the exemplar and prototype theories of categorization
that are either memory-intensive or simplistic in representation. We propose an alternative account of chaining that optimizes cognitive efficiency by trading off representational accuracy with memory complexity. We operationalize this efficient chaining as an infinite mixture model and show how it constructs the internal representations of word meaning adaptively through time while predicting the historical development of English verb meanings with precision and limited resources.

Infinite mixture chaining: Efficient temporal construction of word meaning

Artificial language learning research has shown that, under some conditions, adult speakers tend to probability-match to inconsistent variation in their input, while in others, they regularize by reducing that variation. We demonstrate that this framework can characterize speaker behavior in a natural-language morphological inflection task: 
the lexicon can be used to estimate variation in speaker productions. In the task of German plural inflection, we find that speakers probability-match a lexical distribution conditioned on phonology, and largely disregard an alternative possible strategy of conditional regularization based on grammatical gender.

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

Prior work has shown a “natural” preference in the Verb Phrase for direct object Nouns to linearly precede the Verb. There is also evidence of a “natural” preference in the Noun Phrase to order Nouns before Adjectives. Given this, we asked how domain-general biases like regularization and language-specific biases like the preference for “natural” orders could jointly contribute to the emergence of these two common word orders cross-linguistically. Using a silent gesture paradigm (in which we presented iconic gestures without speech), we exposed different participants to competing Verb Phrase (NounVerb vs. VerbNoun) and Noun Phrase (NounAdj vs. AdjNoun) word orders at varying frequencies. In Noun Phrase contrast conditions, we found that regularization was greatest when the domain-general bias towards regularization and the linguistic bias to order Nouns before Adjectives were aligned. In Verb Phrase conditions, participants regularized to the same extent regardless of input: They opted for greater regularity, even at the expense of aligning with underlying word order biases. We discuss the implications of our work for understanding the effects of domain-general biases on language.

Regularization of Word Order in the Verb Phrase differs from the Noun Phrase: Evidence from an online silent gesture perception paradigm

Languages often express grammatical information through inflectional morphology, in which grammatical features are grouped into strings of morphemes. In this work, we propose that cross-linguistic generalizations about morphological fusion, in which multiple features are expressed through one morpheme, can be explained in part by optimization of processing efficiency, as formalized using the memory--surprisal tradeoff of Hahn et al. (2021). We show in a toy setting that fusion of highly informative neighboring morphemes can lead to greater processing efficiency under our processing model. Next, based on paradigm and frequency data from four languages, we consider both total fusion and gradable fusion using empirical measures developed by Rathi et al. (2021), and find that the degree of fusion is predicted by closeness of optimal morpheme ordering as determined by optimization of processing efficiency. Finally, we show that optimization of processing efficiency can successfully predict typological patterns involving suppletion.

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Categorizing Dogs’ Real World Visual Statistics

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