Netherlands

People frequently encounter the challenge of deciding when to cease exploring options to optimize outcomes, such as when selecting an apartment in a fluctuating housing market or booking a dinner reservation on New Year’s Eve. Despite experiencing these decisions on multiple occasions, people often struggle to stop searching optimally. This research investigates human learning abilities in optimal stopping tasks, focusing on feedback and knowledge of option value distributions. Through an experimental sequential choice task, we demonstrate that experience enhances optimal stopping, with feedback significantly influencing learning. Furthermore, awareness of the value distribution reduces exploration and the duration of the search. A cognitive model accurately predicts these effects, shedding light on human learning processes.

**Authors:**

Erin H. Bugbee: Carnegie Mellon University; Cleotilde Gonzalez: Carnegie Mellon University

CogSci 2024

Feedback Promotes Learning and Knowledge of the Distribution of Values Hinders Exploration in an Optimal Stopping Task

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** 
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** 
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) 
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) 
1415: [Invited Symposium: Dynamics between minds and the environment](https://underline.io/events/465/sessions?eventSessionId=18016&searchGroup=lecture) 
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) 

**Friday, July 26** 
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) 
1030: [Rumelhart Symposium: Childhood as exploration](https://underline.io/events/465/sessions/18038/lecture/100346-childhood-as-exploration) 
1415: [Elman Prize Symposium](https://underline.io/events/465/sessions?eventSessionId=18053&searchGroup=lecture) 
1600: [Invited Symposium: Dynamics between minds](https://underline.io/events/465/sessions?eventSessionId=18065&searchGroup=lecture) 
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) 

**Saturday, July 27** 
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) 
1000: [Glushko Talks](https://underline.io/events/465/sessions?eventSessionId=18086&searchGroup=lecture) 
1500: [Invited Symposium: Dynamics within minds](https://underline.io/events/465/sessions?eventSessionId=18100&searchGroup=lecture) 


#### **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** 
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** 
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.

Object Permanence (OP) is the understanding that objects continue to exist when not directly observable. To date, this ability has proven difficult to build into AI systems, with Deep Reinforcement Learning (DRL) systems performing significantly worse than human children. Here, DRL Agents, PPO and Dreamer-v3 were tested against a number of comparators (Human children, random agents and hard coded Heuristic agents) on 3 object permanence tasks (OP) and a range of control tasks. As expected, the children performed well across all tasks, while performance of the DRL agents was mixed. Overall the pattern of performance across OP and control tasks did not suggest that any agent tested except children showed evidence of robust OP.

**Authors:**

Konstantinos Voudouris: University of Cambridge; Jason Darwin Liu: University of Cambridge; Natasza Siwinska: University of Cambridge; Wout Schellaert: Universitat Politècnica de València; Lucy G Cheke: University of Cambridge

Investigating Object Permanence in Deep Reinforcement Learning Agents

Although we are generally good at observing a busy scene and determining whether it contains one agent pursuing another, we are not immune to making errors and may identify a pursuit when there is none. Further, we may have difficulty articulating exactly what information allowed us to determine whether there was a pursuit. To gain a better measure of when people correctly or erroneously detect pursuit, we designed a novel pursuit detection task. To compare performance given different strategies, we developed a cognitive model that can perform this task. The results of our pursuit detection experiment indicate that, indeed, people typically identify pursuit events correctly, but they make infrequent yet systematic errors for particular scenes. When the model implements specific strategies, simulation results are well correlated with empirical results. Moreover, the model makes the same errors as human participants. We show how the empirical results can be accounted for in terms of decision criteria indicated by high performing model strategies.

**Authors:**

Maria Kon: U.S. Naval Research Laboratory; Sangeet Khemlani: U.S. Naval Research Laboratory; Andrew Lovett: U.S. Naval Research Laboratory

Measuring and Modeling Pursuit Detection in Dynamic Visual Scenes

Previous research with suggests that individuals show prioritized processing for self-referenced stimuli, from self-faces, self-names to momentarily associated arbitrary geometrical shapes. We asked our participants to perform an attentional blink task with self-associated arbitrary geometrical shapes and self-names where these stimuli were either presented as T1(Exp 1A & 2A) or T2 (Exp 1B & 2B). Given that the self-referential shapes would engage more resources a larger attentional blink was expected in Exp1A & 2A, and was found for self-names(2A) as compared to self shapes (1A); however no difference between shapes & names was found when these were presented as the T2 ( Exp 1B & 2B. We conclude that the higher familiarity of self-names drove the larger attentional blink observed with these stimuli and manifested in a bias relative to the control stimuli which were friend and stranger referenced stimuli.

**Authors:**

DIPANJALI YADAV: I.I.T KANPUR; Ark Verma: Indian Institute of Technology Kanpur

Does familiarity drive the self-prioritization effects in attentional processing? Evidence from the Attentional Blink Task.

This research investigates the impact of prolonged oxygen deprivation (approximately 40 minutes) on foundational cognitive capacities such as attention, declarative memory, and executive control. Data was analyzed from twenty-one participants under normoxic and hypoxic conditions performing the psychomotor vigilance test, a paired associates task, and the change signal task. Hypoxia delayed simple visual response times and reduced response inhibition throughout the entire protocol. On the scale of minutes, false starts tended to increase across blocks when participants were hypoxic, but this effect did not carry across blocks. Finally, declarative memory performance was initially unaffected. However, after approximately 20 minutes, hypoxia nearly reversed gains from the first 20 minutes while performance under normoxic conditions continued to improve. The results show a differential susceptibility of different cognitive processes to hypoxia at different time scales and support the use of PVT as a diagnostic for decrements attributed to hypoxia.

**Authors:**

Tim Halverson: Aptima, Inc.; Kara J Blacker: Naval Medical Research Unit - Dayton; Sean Harshman: Air Force Research Lab; Christopher Myers: Air Force Research Laboratory

Differential Cognitive Effects of Extended Hypoxia

When learners improve, the temporal change in performance carries information about progress; we know we "got the hang of it" after succeeding on a task we used to fail at. Building on prior work investigating older children's ability to track their performance over time, here we ask whether two-year-olds can track the temporal pattern of their performance outcomes. Children in the Improvement condition experienced 3 failures followed by 3 successes (FFFSSS) whereas children in the Stochastic condition experienced the same number of failures and successes in a seemingly random sequence (SSFFSF). When asked which toy they wanted to show their parent, children were more likely to select the Test Toy over a Control Toy when the temporal sequence of their performance suggested improvement than when it appeared to be random. These results suggest that two-year-olds can reason about their performance over time and use it to guide their future actions.

**Authors:**

Peter Zhu: Stanford University; Veronica Aranda: Stanford University; Grace E Keene: Stanford University; Hyowon Gweon: Stanford University

Two-year-olds can reason about the temporal structure of their performance

When children solve cognitive problems together, they coordinate their speech, hand movements and head movements. Previous studies with adults have shown that such multimodal coordination is related to better collaboration. We do not know whether this is true for children, however. In this study, dyads of children (6-10 years) discussed and solved balance scale problems together. To investigate children’s multimodal coordination, we measured their speech, hand movements and head movements throughout their bouts of discussion, and applied multidimensional Recurrence Quantification Analysis (MdRQA) on these timeseries. We coded the type of collaboration the children engaged in during these bouts of discussion. We measured performance regarding predicting to which side the balance scale would tilt. We will analyse how children’s multimodal coordination is related to the type of collaboration and to their performance on the balance scale problems. Our results will show how successful collaboration between children emerges from their multimodal coordination.

**Authors:**

Lisette De Jonge-Hoekstra: Psychology, Faculty of Behavioral and Social Sciences, University of Groningen; Wim Pouw: Radboud University; Steffie van der Steen: Faculty of Behavioral and Social Sciences, University of Groningen; Ralf F.A. Cox: University of Groningen; James Dixon: University of Connecticut

Children's multimodal coordination during collaborative problem solving

Trained on text only, Large Language Models (LLMs) provide a unique way to approach the age-old question of how language captures sensory experiences. Such models have showcased human-level performance in several domains. However, what they capture about the sensory world remains uncertain. We prompted state-of-the-art LLMs (GPT-3.5 and GPT-4) as well as sighted and congenitally blind adults to judge the likelihood of successful visual and auditory perception using verbal scenarios. Scenarios varied in distance of the observer from the object (next to, across the street, a block away), duration of perception (glance vs. stare) and properties of perceived object (e.g., size for vision). Sighted and blind humans produced highly consistent perceptibility judgments, and these correlated highly with GPT-3.5 and GPT-4. GPT-4 showed human-like effects of size, distance, and duration, though both LLMs underestimated humans’ ability to perceive. Language captures detailed quantitative information about perceptibility.

**Authors:**

Akshi LNU: Johns Hopkins University; Gabriel Pernell: Johns Hopkins University; Ziwen Wang: Johns Hopkins University; Marina Bedny: Johns Hopkins University

Language captures rich information about perceptibility: Evidence from LMMs and humans

According to prominent accounts of early action understanding, infants’ interpretation of others’ actions is undergirded by an assumption of utility maximization. However, it is unclear whether this assumption applies only to selection among actions or also to selection among goals. Here, using an eye-tracking paradigm, we investigated whether 14- to 16-month-old infants would predict an agent to choose a lower-cost option when faced with two identical outcomes that could be reached at different costs. Infants directed more looks to the lower-cost option, and this effect was not merely due to visual saliency. These findings corroborate the proposal that infants rely on utility maximization when reasoning about an agent’s likely goal and provide evidence of an early ability to represent and compare alternatives in the context of goal attribution.

**Authors:**

Laura Schlingloff-Nemecz: Central European University; Gergely Csibra: Central European University; Denis Tatone: Central European University; Barbara Pomiechowska: University of Birmingham

Infants expect an agent to choose a goal that can be reached at a lower cost

Children learn a lot from others, but the effectiveness of their social learning depends on the reliability of others' help. How do children adapt their future learning decisions based on the past reliability of receiving help? In two experiments, 4- to 6-year-olds (N = 60 each) interacted with a researcher who either followed through on promised help (Reliable condition) or failed to do so (Unreliable condition). Compared to children in the Reliable condition, those in the Unreliable condition were more likely to forego a harder but more rewarding puzzle as their next task and choose an easier, less rewarding puzzle instead. These decisions, while seemingly maladaptive at face value, reflect an adaptive response to the low likelihood of receiving help. These results extend our understanding of social learning across diverse ecological contexts, with broader implications to support education for children in less responsive environments.

**Authors:**

Katherine Adams Shannon: Stanford University; Aneesa Conine-Nakano: Stanford University; Willem E. Frankenhuis: University of Amsterdam; Michael C. Frank: Stanford University; Hyowon Gweon: Stanford University

Young children strategically adapt to unreliable social partners

How does the brain control attention? The Attention Schema Theory suggests that the brain constructs an internal model of attention for its control. However, it remains unclear under which circumstances an attention schema is computationally useful, and whether it can emerge in a learning system without hard-wiring it. To address these questions, we trained a reinforcement learning agent with attention to track and catch a ball in a noisy environment. Crucially, the agent had additional neural resources that it could freely use. We asked under which conditions these additional resources develop an attention schema to track attention. We found that the more uncertain the agent was about the location of its attentional state, the more it benefited from these additional resources, which developed an attention schema. Together, these results indicate that an attention schema emerges in simple learning systems where attention is both important and difficult to track.

**Authors:**

Lotta Marlen Piefke: University Osnabrück; Adrien Doerig: University of Osnabrück; Tim Kietzmann: University of Osnabrück; Sushrut Thorat: Osnabrück University

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