Netherlands

Whether travelling, playing games, or debugging code, any situation where an agent desires change can be framed as a problem. Despite this ubiquity, there is no unifying framework describing how people reason backwards when solving problems. We introduce AND/OR trees, which chain together subgoals and actions to attain them, as a way to represent this process. To investigate whether actions from AND/OR trees were predictive of human behavior, we conducted a study in which participants solved deterministic, long-horizon puzzles. We found that AND/OR trees provided a representation that is predictive of human behaviour. Next, we modeled search through these trees using a psychologically plausible, single-parameter search algorithm. We fit this model to the data of individual participants and found that it captures trends in summary statistics of human play. Our results show the promise of AND/OR trees as a representation for backward reasoning in problem solving.

**Authors:**

Kiera Parece: Harvard University; Sophie Bridgers: MIT; Tomer D. Ullman: Harvard University; Laura Schulz: MIT

CogSci 2024

Exploring Loophole Behavior: A Comparative Study of Autistic and Non-Autistic Populations

### Welcome to the 7th annual workshop on Naval Applications of Machine Learning!

The NAML workshop is an opportunity for researchers from Navy research and development centers and our partner organizations to exchange technical ideas and to come together as a team.

The goals of NAML are:

* To spread awareness of current machine learning research relevant to Naval applications

* To connect machine learning researchers with experts in military requirements

* To build and strengthen collaborations within the defense research community

Naval Information Warfare Center Pacific is partnering with AFCEA San Diego chapter to host the workshop.

**General Chairs:**

Katie Rainey, Naval Information Warfare Center Pacific

Nicole Isoda, Naval Information Warfare Center Pacific<br><br>

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NAML 2023

The 7th annual workshop on Naval Applications of Machine Learning is an opportunity for researchers from Navy research and development centers and our partner organizations to exchange technical ideas and to come together as a team. The goals of NAML are to spread awareness of current machine learning research relevant to Naval applications, to connect machine learning researchers with experts in military requirements and to build and strengthen collaborations within the defense research community.


poster

The 46th Annual Meeting of the Cognitive Science Society was an in-person meeting held in Rotterdam, The Netherlands at the Postillion Hotel & Conference Centre.

**ON-DEMAND PROGRAM ACCESS AFTER THE CONFERENCE**<br>
Recordings of the invited program are now available. You can access them by clicking on the 'Schedule' icon on the left. Select view by week and navigate to the day and time slot of the recording you wish to view. Click on the time slot to access the recording.

Recordings available (click on each recording to view):

**Thursday, July 25**<br>
0900: [Keynote Speaker Morgan Barense on Enhancing real-world event memory](https://underline.io/events/465/sessions/17997/lecture/99084-dynamics-between-minds-and-the-environment)<br>
1000: [Gleitman Award Winner Isabelle Dautriche on Language Foundations: Insights from acquisition, communication, cognition, and more](https://underline.io/events/465/sessions/18000/lecture/99085-gleitman-talk)<br>
1415: [Invited Symposium: Dynamics between minds and the environment](https://underline.io/events/465/sessions?eventSessionId=18016&searchGroup=lecture)<br>
1700: [Rumelhart Prize Presentation Speaker Alison Gopnik on Exploit, explore, empower: Three ages and three intelligences](https://underline.io/events/465/sessions/18028/lecture/99161-rp1-rumelhart-prize-presentation)<br>

**Friday, July 26**<br>
0900: [C.L. de Carvalho-Heineken Prize Keynote Speaker Kia Nobre on Focusing in memory](https://underline.io/events/465/sessions/18035/lecture/99162-hp1-c-l-de-carvalho-heineken-prize-keynote-address)<br>
1030: [Rumelhart Symposium: Childhood as exploration](https://underline.io/events/465/sessions/18038/lecture/100346-childhood-as-exploration)<br>
1415: [Elman Prize Symposium](https://underline.io/events/465/sessions?eventSessionId=18053&searchGroup=lecture)<br>
1600: [Invited Symposium: Dynamics between minds](https://underline.io/events/465/sessions?eventSessionId=18065&searchGroup=lecture)<br>
1745: [Keynote Speaker Andrea E. Martin on Neural dynamics encode the structure and statistics of language](https://underline.io/events/465/sessions/18077/lecture/99271-neural-dynamics-encode-the-structure-and-statistics-of-language)<br>

**Saturday, July 27**<br>
0900: [Keynote Speaker Gregor Schöner on How higher cognition emerges from the dynamics of strongly interacting neural populations](https://underline.io/events/465/sessions/18083/lecture/99273-dynamics-within-the-mind)<br>
1000: [Glushko Talks](https://underline.io/events/465/sessions?eventSessionId=18086&searchGroup=lecture)<br>
1500: [Invited Symposium: Dynamics within minds](https://underline.io/events/465/sessions?eventSessionId=18100&searchGroup=lecture)<br>


#### **CogSci 2024 Program Book**
<div style="position:relative;padding-top:0;width:900px;height:500px;"><iframe style="position:absolute;border:none;width:100%;height:100%;left:0;top:0;" src="https://online.fliphtml5.com/ebtyf/cble/"  seamless="seamless" scrolling="no" frameborder="0" allowtransparency="true" allowfullscreen="true" ></iframe></div>


**The Program Book can be downloaded [here](https://drive.google.com/file/d/1yRVp1cBqRnAbdYi4GXWV_pZeyWNsRquv/view?usp=sharing).**

#### **Letter from the President**

Welcome to the 2024 Meeting of the Cognitive Science Society in Rotterdam! CogSci 2024 brings together a large community of cognitive scientists who have traveled here from around the world, as well as a smaller group of remote presenters. I would like to extend an especially warm welcome to our first-time CogSci meeting attendees, and hope that 
their experience inspires them to join our future meetings for many years to come.

I want to thank this year’s conference co-chairs, Larissa K Samuelson, Stefan Frank, Mariya Toneva, Allyson Mackey, and Eliot Hazeltine, for putting together an amazing series of invited talks and symposia around the theme of Dynamics of Cognition. The co-chairs also deserve credit for handling a record-breaking number of submissions and producing a truly exciting conference program 

Beyond the invited talks and symposia dedicated to this year’s conference theme, I would like to highlight the presentations and events honoring the 
Rumelhart, Elman, Gleitman and C .L . de Carvalho Heineken prize winners, including the Rumelhart reception on Thursday. As you may know, we are recording all of the invited talks and symposia, and all prize-winners’ talks, and will be making this content available after the conference. 

The Cognitive Science Society relies on the volunteer efforts of our Governing Board members who work on matters related to our membership; conference policies; diversity and inclusion, international, and outreach initiatives; prizes and much more. We welcome interest from Society members who would like to become more involved in what we do. The 
Society is deeply grateful to Rick Dale and Andrea Bender, who serve as editors of the two Society journals, Cognitive Science and Topics in Cognitive Science respectively. We especially acknowledge our editors’ generosity in donating their stipends each year to D&I and outreach efforts. 

This year’s Annual Meeting depends critically on the support of Marischal De Armond and his team at Podium Conference Specialists: Sharon Zwack, Cendrine De Vis, Sarah-Kate Burke, and Rachel Waller worked tirelessly to secure the venue and handled a multitude of logistical and organizational issues, from arranging coffee breaks and receptions to making sure that a huge number of posters fits comfortably into the available space. Finally, and importantly, I would like to acknowledge the Cognitive Science Society Executive Officer, Erica Wojcik, for managing the complex and ever expanding sphere of our Society’s activities.

I hope you enjoy this year’s meeting and the many different opportunities to engage with the vibrant community of cognitive scientists gathered here. I also hope you get a chance to explore the great city of Rotterdam with its many attractions, museums, restaurants and scenic views. If you’d like to talk more about our Society, or simply want to say hello, please stop by!

![](https://assets.underline.io/markdown_image/1/image/3c66d0e21fff30e204df1138ffd15173.jpeg)

**Anna Papafragou**  
President, Cognitive Science 
Society 2023-2024

**CODE OF CONDUCT**<br>
By attending the CogSci 2024 Conference, you are required to adhere to the society’s [Code of Conduct](https://drive.google.com/file/d/16-6KkptF0Gn3ZYGJDlpqpwTdImw45Ng0/view?usp=drive_link).

**ABOUT THE COGNITIVE SCIENCE SOCIETY**<br>
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.
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The 46th Annual Meeting of the Cognitive Science Society presents the latest research across cognitive science and highlights the theme of Cognition in Context.

Large language models (LLMs) were trained to predict words without having explicit semantic word representations as humans do. Here we compared LLMs and humans in re-solving semantic ambiguities at the word/token level by ex-amining the case of segmenting overlapping ambiguous strings in Chinese sentence reading, where three characters “ABC” could be segmented in either “AB/C” or “A/BC” depending on the context. We showed that although LLMs performed worse than humans, they demonstrated a similar interaction effect between segmentation structure and word frequency order, suggesting that this effect observed in humans could be accounted for by statistical learning of word/token occurrence regularities without assuming an explicit semantic word representation. Nevertheless, across stimuli LLMs’ responses were not correlated with any hu-man performance or eye movement measures, suggesting differences in the underlying processing mechanisms. Thus, it is essential to understand these differences through XAI methods to facilitate LLM adoption.

**Authors:**

Jeroen Olieslagers: New York University; Zahy Bnaya: myWhatIf foundation; Yichen Li: Harvard University; Wei Ji Ma: New York University

Backward reasoning through AND/OR trees to solve problems

A field study examined how strongly the three categories of epistemically unwarranted beliefs: pseudoscience, conspiracist, and paranormal beliefs, can be predicted by cognitive ability in participants from several European countries. Each type of beliefs was significantly and strongly correlated with the remaining two types of beliefs, but only weakly related with cognitive ability, suggesting a minor role of reasoning and problem solving processes for forming and holding unwarranted beliefs. A role of cognitive ability for rejecting unwarranted beliefs was stronger in males than in females.

**Authors:**

Weiyan Liao: University of Hong Kong; Zixuan Wang: City University of Hong Kong; Kathy Shum: University of Hong Kong; Antoni B. Chan: City University of Hong Kong; Janet Hsiao: Hong Kong University of Science & Technology

Do large language models resolve semantic ambiguities in the same way as humans? The case of word segmentation in Chinese sentence reading

In similarity comparisons, people often show a preference for one direction over the other. Bowdle and Gentner (1997) proposed the base systematicity account to explain this—namely, that people prefer similarity comparisons in which the more systematic item serves as the base. Results from a series of studies supported this account. However, the studies only covered literal similarity comparisons. The question of whether analogical comparison follows the base advantage pattern remained untested. Therefore, the present study investigated this question for analogical comparisons. We tested the prediction that a comparison will be preferred when the more systematic item serves as the base. This prediction was supported. We also found support for a further prediction: namely, that inferences were projected from the systematic to the less systematic passage. Further, these inferences spontaneously arose even when not requested. The overall results from these processes are consistent with the base systematicity advantage account.

**Authors:**

Jan Jastrzebski: Jagiellonian University; Adam Chuderski: Jagiellonian University; Hanna Kucwaj: SWPS University

Is Cognitive Ability Related with Rejecting Pseudoscience, Conspiracist, and Paranormal Beliefs? A Field Study

Theory of mind is often referred to as “belief-desire” psychology, as these mental states (belief, desire) are accorded a central role. However, extant research has made it clear that defining the notion of belief or characterizing a consistent set of key characteristics is no trivial task. Across two studies (N=283, N=332), we explore the hypothesis that laypeople make more fine-grained distinctions among different kinds of “belief.” Specifically, we find evidence that beliefs with matching contents are judged differently depending on whether those beliefs are seen as playing predominantly epistemic roles (such as tracking evidence with the aim of forming accurate representations) versus non-epistemic roles (such as social signaling). Beliefs with epistemic aims, compared to those with non-epistemic aims, are more likely to be described with the term “thinks” (vs. “believes”), and to be redescribed in probabilistic (vs. binary) terms. These findings call for a refinement of the concepts posited to underly theory of mind and offer indirect support for the idea that human psychology in fact features more than one kind of belief.

**Authors:**

Fanyi Mo: Northwestern University; Dedre Gentner: Northwestern University

Exploring Analogical Asymmetry

Understanding how people represent similarity relations between concepts is one of the most fundamental problems in cognitive science, with implications for many theories of learning and reasoning. Human judgements of similarity violate basic metric assumptions, leading to effects such as judgment asymmetry and the triangle inequality. These effects have been difficult to capture with modern geometric representations of conceptual structure such as vector embeddings. Here we introduce a set-based metric related to the prototype view of concepts. We show how this metric can be applied to geometric representations and that the resulting algorithm can account for classic judgment effects. Using representations extracted from a Large Language Model, we computed the predictions of this approach to similarity relations among a set of everyday concepts (world countries) and evaluated these predictions against human judgements of similarity in a behavioral experiment. The model's predictions correlate with human judgements, and outperform alternative models. These results offer insight into human judgements of similarity relations and the design of algorithms that align with human reasoning.

**Authors:**

Alejandro Vesga: Princeton University; Neil Van Leeuwen: Georgia State University; Tania Lombrozo: Princeton University

Evidence for distinct cognitive attitudes of belief in theory of mind

People use incomplete social network information to infer relationships. For example, if two individuals have many mutual friends, people infer they are friends with each other. We examined whether these inferences depend on domain-specific knowledge about social relationships, or instead depend on domain general-reasoning about statistics and proportions. In two experiments, participants (N=526) either saw partial information about social networks, like friendships between people, or about non-social networks, like wired connections between electrical parts. They then judged if two entities in each network were directly connected to each other. The entities varied in the number of connections and the proportion of mutual connections. People made similar judgments across social and non-social networks: with greater proportion of mutual connections, the two entities were judged as more likely to be connected to each other. In sum, inferences about networks might primarily depend on reasoning about statistics and proportions.

**Authors:**

Karthikeya Ramesh Kaushik: University of California, Berkeley; Bill Thompson: University of California, Berkeley

Modelling metric violations in (geometric) conceptual spaces

Diversity, equity, and inclusion (DEI) initiatives are widespread and well-intentioned within progressive institutions. However, many such initiatives backfire because they diminish external perceptions of diverse hires' competence. Across five preregistered experiments, we develop a novel theory: that statistical reasoning about candidate competence is clouded in DEI cases by existing priors and stereotypes, as well as mentalistic assumptions about selector intention. Supporting this, we find that people do make logical statistical inferences with uniform populations and random selection processes. However, as people receive more information about the population and the selection process, their decisions move away from optimality. This work will inform interventions to tailor DEI messaging. While it is difficult to entirely eliminate people's existing stereotypes and priors, it may be feasible to intervene on their statistical intuitions in response to DEI initiatives.

**Authors:**

Claudia G. Sehl: University of Waterloo; Ori Friedman: University of Waterloo; Stephanie Denison: University of Waterloo 

Inferences about social networks using domain-general reasoning

Peak shifting is a key method to enhance the resilience of water supply infrastructure. Due to limitations related to the cost of smart meters, experimentally investigating the impact of a time-of-use tariff on inducing peak shifting in water usage has been challenging. Having experimentally introduced smart meters across 1,890 households, this study investigated behavioral responses to reduced water prices during off-peak hours (i.e., by increasing the relative cost of peak-time usage). This was achieved by implementing a pricing scheme offering a 60% discount from 23:00 to 05:59 and a 20% discount from 10:00 to 16:59. The results revealed significant changes in water usage behavior near the boundary between off-peak and peak times, suggesting a shift in water usage behavior towards the off-peak period. Moreover, a time-series analysis demonstrated peak shifting induced by off-peak price reductions. Furthermore, this study examines cognitive processing and its impact on altering water usage behaviors on an hourly basis. These findings suggest that reducing prices during off-peak periods can effectively induce peak shifting across a broad range of times.

**Authors:**

Aarthi Popat: Yale University; Yarrow Dunham: Yale University

“I’m going to choose a Hibble”: Social and statistical reasoning in DEI contexts

In syllogistic reasoning research, humans are predominantly evaluated on their capabilities to judge whether a conclusion necessarily follows from a set of premises. To tackle this limitation, we build on work by Evans, Handley, Harper, and Johnson-Laird (1999), and present two studies where we asked participants for possible and likely conclusions. Combined with previous data (containing necessary), we present a comprehensive dataset with responses for all syllogisms, offering individual patterns for all three argument types – a first of its kind. We discovered that likely serves as a middle ground between possible and necessary, paving the way to further investigate biases and preferences. Generally, individuals were able to handle the different notions, yet tended to interpret quantifiers in a pragmatic way, overlooking logical implicatures. Finally, we tested mReasoner, an implementation of the Mental Model Theory, and concluded that it was not able to capture the patterns observed in our data.

**Authors:**

Yutaro Onuki: Hitotsubashi University; Yurina Otaki: Hitotsubashi University

Off-Peak Price Reductions for Water Demand Management

This study investigates the interaction between semantic relatedness and goals or task on memory retrieval. We used varied tasks and concepts to explore how task influences how different kinds of semantic relatedness influences semantic processing. Our findings reveal a task-dependent interaction with semantic relatedness. Specifically, in similarity judgement tasks (experiments 1a and 1b), participants' ratings closely aligned with taxonomic relatedness, influenced by abstract visual and linguistic similarity dimensions. In discrimination tasks (experiments 2a and 2b), where participants distinguished a target from a semantically related distractor, visual characteristics explained a greater amount of variance. These results suggest semantic memory representations are dynamic and task-dependent, supporting theories of a distributed semantic memory system.

**Authors:**

Daniel Brand: Chemnitz University of Technology; Sara Todorovikj: University of Technology Chemnitz; Marco Ragni: TU Chemnitz

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