Canada

**Abstract:**

The ancient Greek hero Ulysses chose to bind himself to resist the temptation of Sirens, highlighting the fact that humans may voluntarily sacrifice their freedom of choice to achieve committed goals. In this work, we propose a computational model for such commitment under the framework of Bayesian Theory of Mind. The model is based on the idea that even when alone, humans act to better demonstrate their intentions to an imagined third-party observer (ITO) censoring their actions. Our model successfully captures the Ulysses-constraint of freedom, as the freedom confuses the ITO’s inference of their intention. We further show that, trajectories generated both by human actors and actors modeled with ITO censorship are easy to interpret both in the eyes of an actual human ob- server and an ITO. The results demonstrate that under conflict- ing desires, humans achieve commitment by spontaneously censoring their actions with an internalized theory of mind.

**List of authors and affiliations:**

Shaozhe Cheng: Zhejiang University; Minglu Zhao: University of California - Los Angeles; Jingyin Zhu: Zhejiang University; Jifan Zhou: Zhejiang University; Mowei Shen: Zhejiang University; Tao Gao: UCLA

CogSci 2022

Intentional commitment through an internalized theory of mind: Acting in the eyes of an imagined observer

poster

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.
 
 [**The Program at a Glance can be found here**](https://cognitivesciencesociety.org/wp-content/uploads/2022/07/Cogsci-2022-PAAG-Detailed-July-12final-1.pdf)
 [**The Detailed Program can be found here**](https://cognitivesciencesociety.org/wp-content/uploads/2022/08/DeArmond-CogSci2022-program-v113-final.pdf)

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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. 





**Abstract:**

People collaborate daily to achieve joint goals, negotiating sidewalks, preparing meals, constructing furniture. Here we analyzed how strangers coordinate a complex novel task, assembling a TV cart. Before beginning and before major actions, partners used a photo of the completed cart, speech, and gesture to establish a joint model of the structure of the completed cart. Most coordination was implicit, a conversation of actions that could be understood in the context of the current state of the object and the shared mental representation. Actions served a dual purpose, both to communicate and to advance the task. The basic unit of coordination was the dyad, not the individual.

**List of authors and affiliations:**

Chen Zheng: Teachers College, Columbia University; Barbara Tversky: Columbia Teachers College

Explicit and Implicit Coordination of Joint Action

**Abstract:**

Although pointing is sparse, overloaded, and indirect, it allows humans to effectively decode shared information, (ex)change their minds, and plan accordingly. Pointing is an invitation to jointly attend to an object, which triggers the mutual inference between agents of each other’s mind. Relevance is a fundamental assumption underlying all human communication, including pointing. We define relevance as how much a signaler’s belief can make a positive difference to its receiver’s well being. We build a Theory of Mind (ToM) model to test our definition of relevance and use pointing as a case study. In two experiments, we test our relevance model in a classic artificial intelligence (AI) task, the Wumpus world, with the key difference that there is a guide that points to help a hunter. Agents with our relevance model gain significantly higher rewards than agents who ignore signals from the guide. Agents with our model also achieve better performance than agents who receive an additional observation of the environment. The results show that the power of pointing comes from the ToM inference of relevance, rather than providing more precise individual perception.

**List of authors and affiliations:**

Kaiwen Jiang: University of California, Los Angeles; Stephanie Stacy: University of California - Los Angeles; Annya L. Dahmani: University of California - Los Angeles; Boxuan Jiang: University of California, Los Angeles; Federico Rossano: University of California, San Diego; Yixin Zhu: UCLA; Tao Gao: UCLA

What Is the point? a Theory of Mind Model of Relevance

**Abstract:**

Testing on previously learned materials can enhance the learning of new materials studied after the test (the forward effect of testing). We examined how the timing of interim testing influenced subsequent learning. Participants studied trivia facts in two learning sections (A & B) and provided a mental effort rating for each section. Between the two sections, participants either restudied, took an immediate test, or a 15-min delayed test on Section A. They then proceeded to Section B and took a final test on both sections. The results demonstrated that both the immediate and delayed testing groups outperformed the restudy group on Section B, indicating that the forward effect of testing was independent of the test timing. Furthermore, the testing groups showed a bigger increase in their mental effort from Section A to B than the restudy group, suggesting that the forward testing effect occurred probably due to more mental effort.

**List of authors and affiliations:**

Yewon Kang: Yonsei University; Hee Seung Lee: Yonsei University

Does delayed interim testing enhance subsequent learning?

**Abstract:**

Computational cognitive theories of Autism Spectrum Disorder have received renewed attention in recent years. Consistent with the predictive processing framework, ASD has
been re-conceptualized as a disorder of aberrant prediction and learning-rate estimation involving multiple levels of a putative cognitive computational hierarchy. Specifically, behavioral symptoms of individuals with ASD might manifest due to an aberrant overestimation of the volatility of environmental contingencies (i.e. tendency of change in cue-outcome probabilities) which in turn might induce a dysfunctional setting of learning rates. In this work, we attempted to conceptually replicate computational modeling analyses of an impactful study of the recent ASD modeling literature in an independent
sample of subjects. We were not able to replicate some prior reported effects likely due to differences in model architecture and cognitive task setup. We found statistical trends in similar directions.

**List of authors and affiliations:**

Hauke Niehaus: University Marburg; Sanna Stroth: Philipps University Marburg; Inge Kamp-Becker: Philipps University Marburg; Dominik M Endres: Philipps-Universitaet

Modeling aberrant volatility estimates in Autism Spectrum Disorder

**Abstract:**

While problem-solving is central in our daily life, its underlying mechanisms remain elusive. The dominant theory states that one must restructure a problem (i.e., reorganize problem-related representations) to solve it. As empirical evidence supporting this mechanism is scarce, we used network science methodology to demonstrate the key role of restructuring in problem-solving. Individual semantic memory networks were estimated before and after participants attempted to solve a riddle. These networks represent the organization of solution-relevant and irrelevant words as nodes, with edges representing the strength of the relationship between them based on the participants’ relatedness judgments. Restructuring was quantified as the difference in semantic network metrics between pre- and post-solving phases. Successful problem-solving was predicted by local semantic network restructuring, only in edges and nodes assessed as helpful to solve the riddle. These results shed new light on the mental restructuring in problem-solving and provide a new method to quantify it.

**List of authors and affiliations:**

Théophile Bieth: Paris Brain Institute, Sorbonne university; Yoed Kenett: Technion - Israel Institute of Technology; Marcela Ovando Tellez: Paris Brain Institute, Sorbonne university; Celia Lacaux: Paris Brain Institute, Sorbonne university; Delphine Oudiette: Paris Brain Institute, Sorbonne university; Emmanuelle Volle: Paris Brain Institute, Sorbonne university

Restructuring problem-related semantic associations promotes solving success

**Abstract:**

Logico-semantic theories have long noted parallels between the linguistic representation of temporal entities (events) and spatial entities (objects): bounded (or telic) predicates such as fix a car resemble count nouns such as sandcastle because they are “atoms” with well-defined boundaries. By contrast, unbounded (or atelic) phrases such as drive a car resemble mass nouns such as sand in that they are unspecified for atomic features. Here, we show for the first time that there are similarities in the perceptual-cognitive representation of events and objects in non-linguistic tasks. Specifically, after viewers form a bounded or an unbounded event category, they can extend the category to objects or substances respectively (Experiment 1). Furthermore, viewers can intuitively make event-to-object mappings that respect atomicity (Experiment 2). These striking similarities between the mental representation of events and objects have implications for current theories of event cognition, as well as the relationship between language and thought.

**List of authors and affiliations:**

Yue Ji: Beijing Institute of Technology; Anna Papafragou: Unversity of Pennsylvania

Events and Objects Are Similar Cognitive Entities

**Abstract:**

Events are considered as temporal segments with a beginning and an endpoint. Philosophical and linguistic literature on events distinguishes between bounded events that include distinct temporal stages leading to culmination (e.g., fix a car) and unbounded events that include largely undifferentiated stages and lack an inherent endpoint (e.g., drive a car). The present study shows that event viewers spontaneously compute this distinction through an interruption detection task. People watched videos of bounded or unbounded events with a visual interruption lasting .03s at the midpoint or close to the endpoint of the event stimulus. People indicated whether they saw an interruption after each video (Experiments 1) or responded as soon as possible during each video (Experiment 2). In both cases, the endpoint-midpoint difference depended on whether participants were watching a bounded or an unbounded event. As people perceive dynamic events, they spontaneously track boundedness, or the internal temporal structure of events.

**List of authors and affiliations:**

Yue Ji: Beijing Institute of Technology; Anna Papafragou: Unversity of Pennsylvania

Viewers Spontaneously Represent Event Temporal Structure

**Abstract:**

Motion lines are the drawn lines trailing behind an object to show movement. Prior work has shown that motion lines aid comprehension by clarifying the direction of motion, but no experimental research has examined how they interact with path segmentation, like a visual sequence in comics. In Experiment 1, participants understood panels with motion lines better than without lines. With motion lines, omitting the path’s source was harder to comprehend than showing the source but having it disappear. Moreover, less experienced comic readers benefited more from showing a whole path with lines in single panels than fluent ones. In Experiment 2, reversed-direction lines were harder to process than normal or omitted lines, but segmentation did not matter. Overall, motion event comprehension can be modulated by path segmentation of lines and comics reading experience.

**List of authors and affiliations:**

Irmak Hacımusaoğlu: Tilburg University; Neil Cohn: Tilburg University

Motion Event Segmentation in Visual Narratives

**Abstract:**

Previous research demonstrated an asymmetry between Sources and Goals in people’s linguistic and non-linguistic encoding of motion events: when describing events such as a fairy going from a tree to a flower, people mention the Goal (“to a flower”) more often than the Source (“from a tree”) and are better at detecting Goal changes in a Same-different memory test. Many take these findings as evidence for a homology between linguistic and conceptual representations: an unmentioned event component is also conceptually less robust. Here, we show that the nonlinguistic Source-Goal asymmetry disappears when memory is probed with a Forced-choice task instead of a Same-different task. We argue that, despite frequent absence from linguistic descriptions, Sources are robust in event memory, but not attended to during Same-different tests due to people’s task-relevance assumption. This result bears on the nature of the Source-Goal asymmetry and calls for a finer-grained account for language-cognition homology.

**List of authors and affiliations:**

Yiran Chen: University of Pennsylvania; John Trueswell: University of Pennsylvania; Anna Papafragou: Unversity of Pennsylvania

The Source-Goal Asymmetry in Motion Events: Sources Are Robustly Encoded in Memory but Overlooked at Test

**Abstract:**

Human social interactions require understanding and predict- ing other people’s behavior. A growing body of work has found that these inferences are structured around an assumption that agents act rationally and efficiently in space. While powerful, this view treats action understanding in a vacuum, ignoring that much social inference happens in the context of familiar, hierarchically structured events (e.g.: buying groceries, ordering in a restaurant). We propose that social and world knowledge is critical for efficiently interpreting behavior and test this idea through a simple block-building paradigm, where participants infer an agent’s sub-task (study 1a), next action (study 1b), and higher-level goal (study 1c), from very sparse observations. We compare these inferences against a Bayesian model of goal inference that exploits task structure to interpret agents’ actions. This model fit participant judgments with high quantitative accuracy, highlighting how world knowledge may help support social inferences in a rich and powerful way.
Keywords: Computational modeling; Social cognition

**List of authors and affiliations:**

Isaac Davis: Yale University; Julian Jara-Ettinger: Yale University

Intentional commitment through an internalized theory of mind: Acting in the eyes of an imagined observer

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Explicit and Implicit Coordination of Joint Action

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