Tversky and Kahneman (1973) found that, under time pressure, people massively underestimated the expansion of 8! (correct value 40,320), and this bias was mitigated for participants presented the descending (8x7x6x5x4x3x2x1; Median=2,250) vs. ascending order (1x2x3x4x5x6x7x8; Median=512). In a first-ever replication (N=140), we also found predominant underestimation, but no significant between-subjects descending vs. ascending order effect. However, when participants then estimated the opposite order, we reproduced this order effect within-subjects. Finally, participants received calibration information (the correct value of 6! or 10!) and again estimated both orders of 8!. Participants who received 10! made more accurate estimates for 8! (Median=38,000), which did not differ statistically from the correct value. Participants who received 6! still grossly underestimated (Median=2,678.5), despite 8! being closer to 6! than 10! in linear and log units. Thus, we surprisingly found the classic factorial estimation bias only within-subjects, and provide evidence for how calibration can reduce it.

Calibration information reduces bias during estimation of factorials: A (partial) replication and extension of Tversky and Kahneman (1973)

Human solutions to the Traveling Salesperson Problem (TSP) are surprisingly close to optimal and unexpectedly efficient. We posit that humans solve instances of the TSP by first clustering the points into smaller regions and then solving each cluster as a simpler TSP. Prior research has shown that participants cluster visual stimuli reliably. That is, their clustering and re-clustering of the same stimulus are similar, especially when the stimulus is relatively more clustered. In this study, participants solved the same TSP instances twice. On the second presentation, half of the instances were flipped about the horizontal and vertical axes. Participants solved the TSP reliably, with their two tours of the same instance sharing 77 percent of the same edges on average. In addition, within-participant reliability was higher for more clustered versus more dispersed instances. Our findings are consistent with the proposal that people use clustering strategies to solve the TSP.

The role of clustering in the efficient solution of small Traveling Salesperson Problems

Traditional statistics instruction emphasizes a .05 significance level for hypothesis tests. Here, we investigate the consequences of this training for researchers’ mental representations of probabilities –– whether .05 becomes a boundary, i.e., a discontinuity of the mental number line, and alters their perception of differences between p-values. Graduate students (n = 25) with statistical training viewed pairs of p-values and judged whether they were ‘similar’ or ‘different’. After controlling for covariates, participants were more likely and faster to judge p-values as ‘different’ when they crossed the .05 boundary (e.g., .047 vs. .052) compared to when they did not (e.g., .027 vs. .032). This categorical perception effect suggests that traditional statistical instruction creates a psychologically real divide between so-called statistically significant and non-significant p-values. Such a distortion is undesirable given modern approaches to statistical reasoning that de-emphasize dichotomizing p-values.

Categorical perception of p-values

How humans visually cluster points is potentially relevant to perception, information visualization, and other areas. However, there are relatively few empirical studies and computational models of this ability. Here, we propose a new competitive clustering_ model that uses neurally plausible mechanisms such as hebbian learning and lateral inhibition. We evaluate its fit to the data from a behavioral study of visual clustering, as well as the fits of two categorization models (the Rational model and SUSTAIN) and $K$-Means. We find that people are highly reliable in their clusterings of the same stimulus on two occasions, suggesting they are using a stable strategy. The models were generally successful at predicting human clusterings and were able to replicate the qualitative performance profile of human reliability over number of points and over cluster structure. The performance of the competitive clustering model motivates further investigation of its computational properties and empirical validity.


Models of human visual clustering

Problem solving under time and material constraints assumes that humans face both their own internal computational limitations and constraints of the external task environment. To find optimal solutions under these constraints, the agent must adapt their behavior by using various strategies such as offloading (i.e., using external materials to aid their performance). We designed a novel tower building task to investigate adaptive use of strategies under constraints. The task worked as designed: Participants found the optimal solution most often on the least difficult scenario and least often on the most difficult scenario. Surprisingly, offloading led to no significant differences in performance. However, on the most difficult scenario, some participants found the optimal solution using a prospective, concurrent, or retrospective strategy based on experience with the constraints of the task environment. We conclude that optimality can be understood as a trend over time and investigated in studies that allow multiple attempts.

Adaptivity and optimization under constraints


**For a full list of posters in this session, click the See All link on the right side of the page.**

Poster Session 1 -  C : Cognitive Science

poster

### Looking for Cogsci 2023? Please [click here](https://underline.io/events/405/reception) to switch to 2023 edition.


**Dear Colleagues,**

Welcome to the 43rd Annual Conference of the Cognitive Science Society! 

This year’s conference brings together the latest research from all Cognitive Science and also highlights this year’s theme **Comparative Cognition: Animal Minds.** 

The program features four plenary speakers: Friederike Range (University of Veterinary Medicine, Vienna), Onur Güntürkün (Ruhr University Bochum), Julia Fischer (University of Göttingen), and Erich Jarvis (The Rockefeller University). The keynotes and invited symposia showcase the broad spectrum of ideas that encompass the conference theme of comparative cognition. 

Further, the program includes the Rumelhart Prize keynote presentation by Susan Goldin-Meadow (University of Chicago), and symposia to celebrate the winner of the Elman Prize: Wei Ji Ma (New York University), the Heineken Award winner Robert Zatorre (McGill University), and the Robert J. Glushko Dissertation Prizes session.

The program committee for CogSci 2021 received 1,025 submissions, including 710 full papers, 275 member abstracts, 8 publication-based talks, as well as 15 proposals for symposia, and 17 for workshops and tutorials. After a rigorous review process, the committee selected 152 papers for oral presentation and inclusion in the conference proceedings (14.8%), 332 papers for poster presentation and inclusion in the proceedings (32.4%), and 175 papers for poster presentation with inclusion of abstracts in the proceedings (17.1%) We also selected 275 submitted member abstracts. In addition, we accepted 6 publication-based talks, 12 symposia, and 9 workshops and tutorials to make for an exciting and inclusive program.

We hope that you enjoy the conference this year! 

**Your Program Chairs,**
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**Learn more about the Vienna Cognitive Science Hub at the University of Vienna, hosts of CogSci 2021**

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To review the proceedings for the conference or review the searchable program, please visit the [website](https://cognitivesciencesociety.org/program/).

CogSci 2021

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.



**For a full list of posters in this session, click the See All link on the right side of the page.**

Poster Session 2 -  A: AI, Computer Science and Computer Models

**Session Chair: **Gary Lupyan 
**Technical Session Chair: **Raihyung Lee 
**Session Description: ** The session is comprised of 15 minute talks followed by up to 5 minutes of live Q&A time for each presenter.

IP5: Categorization

technical paper

This session has no scheduled virtual poster presentation time, but attendees will be able to comment and ask questions about your work/research asynchronously throughout the conference. 

**If you are a virtual poster presenter**, you can leave a message in your poster area chat space to advise times (and time zone) that you will be available either in the chat box, or by setting up your own online meeting room (Zoom, etc.). 
**If you are an attendee**, please check each poster's chat box and arrange time with presenter.

Virtual Posters

The 45th Annual Meeting of the Cognitive Science Society will take place in Sydney, Australia as a modified hybrid conference. Presentations from the main-session room will be live-streamed every day for all events. This will include all invited talks and award sessions. Recordings of all CogSci 2023 sessions will be made available for on-demand viewing after the conference. 
The in-person component will be held at the International Convention Centre Sydney at Darling Harbour. The Conference will take place Wednesday July 26th – Saturday July 29th, 2023 (Wednesday, July 26th is the Workshops Day).

Join us!

 [**The Program at a Glance can be found here**](https://cognitivesciencesociety.org/wp-content/uploads/2023/07/COgSci-PAAG-V2.pdf)
 [**The Detailed Program can be found here**](https://online.fliphtml5.com/ebtyf/mswz/)
 

#### **CogSci 2023 Program Book**
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CogSci 2023

The 45th Annual Meeting of the Cognitive Science Society presents the latest research across cognitive science and highlights the theme of Cognition in Context.

Sashank Varma

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Presentations

Calibration information reduces bias during estimation of factorials: A (partial) replication and extension of Tversky and Kahneman (1973)

The role of clustering in the efficient solution of small Traveling Salesperson Problems

Categorical perception of p-values

Models of human visual clustering

Adaptivity and optimization under constraints

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