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In this study, we explicitly code and study the social, referential, and pragmatic features of gaze in human-human spontaneous dyadic interaction, providing novel observations that can be executed in a machine in order to improve multimodal human-agent dialogue. Gaze is an important non-verbal social signal that contains attentional cues about where to look and provides information about others&#39; intentions and future actions. In this work, various types of gaze behaviour are annotated in detail along with speech to explore the meaning of temporal patterns in gaze cues and their co-relations. Considering that 80% of the total stimuli perceived by the brain is visual, gaze behaviour is complex and challenging; hence, implementing human-human gaze cues to an avatar/robots could improve human-agent interaction and make it more natural.

CogSci 2021

A Deep Gaze into Social and Referential Interaction

The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines. AAAI-23 is the Thirty-Seventh AAAI Conference on Artificial Intelligence. The theme of this conference is to create collaborative bridges within and beyond AI. Like previous AAAI conferences, AAAI-23 will feature technical paper presentations, special tracks, invited speakers, workshops, tutorials, poster sessions, senior member presentations, competitions, and exhibit programs, and two new activities: a Bridge Program and a Lab Program. Many of these activities are tailored to the theme of bridges and all are selected according to the highest standards, with additional programs for students and young researchers.<br><br><br>
AAAI is providing you with a conference planner, which you can use to help organize your itinerary of activities.  This includes talks to attend in person, talks to attend remotely, breaks with colleagues  and your site seeing activities. To access this conference planner, please go to [https://aaai-2023.takemobi.io](https://aaai-2023.takemobi.io).<br><br><br><br>

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AAAI 2023

The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines.

In this study, we explicitly code and study the social, referential, and pragmatic features of gaze in human-human spontaneous dyadic interaction, providing novel observations that can be executed in a machine in order to improve multimodal human-agent dialogue. Gaze is an important non-verbal social signal that contains attentional cues about where to look and provides information about others' intentions and future actions. In this work, various types of gaze behaviour are annotated in detail along with speech to explore the meaning of temporal patterns in gaze cues and their co-relations. Considering that 80% of the total stimuli perceived by the brain is visual, gaze behaviour is complex and challenging; hence, implementing human-human gaze cues to an avatar/robots could improve human-agent interaction and make it more natural.

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### 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!<br><br>

**Your Program Chairs,**
![](https://assets.underline.io/uploads/markdown_image/1/image/99984908caba5e6453e5fc5ba34f3507.jpg)

**Learn more about the Vienna Cognitive Science Hub at the University of Vienna, hosts of CogSci 2021**

<iframe width="560" height="315" src="https://www.youtube.com/embed/464h1m3iU68" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>

To review the proceedings for the conference or review the searchable program, please visit the [website](https://cognitivesciencesociety.org/program/).


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.

Recent studies have applied network-based approaches to analyze the organization and retrieval of specific semantic categories, with a focus on the animal category. The current study extended previous studies by using network science tools to quantitatively investigate the structural differences of noun and verb categories of various levels of specificity. Specific (animal and body movement) and general noun and verb networks were constructed from four verbal fluency tasks. Common network measures indicated that the two verb networks were more condensed and less modular than the noun networks, supporting that nouns are more well-organized in the mental lexicon than verbs. Comparing the specific and general networks within each lexical category also corroborated lexical semantic studies that nouns have a more clear hierarchical structure. The results of this paper, along with recent semantic network studies, provide converging evidence for the usefulness of network science in semantic memory research.

Structural Comparisons of Noun and Verb Networks in the Mental Lexicon

In a high-risk environment, such as during an epidemic, people are exposed to a large amount of information, both accurate and inaccurate. Following exposure, they typically discuss the information with each other in conversations. Here, we assessed the effects of such conversations on their beliefs. A sample of 126 M-Turk participants first rated the accuracy of a set of COVID-19 statements (pre-test). They were then paired and asked to discuss either any of these statements (low epistemic condition) or only the statements they thought were accurate (high epistemic condition). Finally, they rated the accuracy of the initial statements again (post-test). We did not find a difference of epistemic condition on belief change. However, we found that individuals were sensitive to their conversational partners and changed their beliefs according to their partners’ conveyed beliefs. This influence was strongest for initially moderately held beliefs.

The Effects of Dyadic Conversations on Coronavirus-Related Belief Change

A key element of conceptual understanding in physics education is the ability to make qualitative inferences. In this study, we investigated whether people use causal notions when solving simple, qualitative physics problems. We utilized the principles of directionality and holding variables constant to assess participant's accuracy in answering questions about inferences from cause to effect (CE), effect to cause (EC), and from one cause to the other cause (CC). Participants responded with greater accuracy for CE and EC questions when alternative causal information was held constant compared to when it is made explicitly unknown. For CC questions accuracy was lower across all alternative information types. Further, participants generally treated ambiguous alternative causes as if they were held explicitly constant. These results indicate that using notions of causality can potentially help identify difficult qualitative physics questions and be used as a tool in instructional design.

Using Causality to Map Difficulties in a Qualitative Physics Problem

Previous studies investigating the influence of a working memory load on category learning gained mixed findings. The current study investigated the role of increased working memory load in the processes of encoding two artificial categories with a rule-plus-similarity structure. During category learning, adults were trained with a dual-task that integrated the category learning task with a secondary working memory task. Participants were instructed to retain verbal (auditorily delivered) information while learning the categories in each trial. The learning phase was followed by recognition and categorization tasks evaluating their learning of the categories and memory for exemplar features. The results indicated that verbal working memory load affected category learning and representation as compared to the control condition where participants learned the categories without interference. The dual-task paradigm disrupted attention optimization and the formation of a rule-based category representation while increasing the probability of similarity-based encoding.

Verbal working memory capacity modulates category representation.

A set of fundamental beliefs governs our reasoning about objects and agents since infancy. Studies have shown that infants and children show enhanced exploration and learning when they observe apparent violations of these beliefs. However, little is known about whether these beliefs can be revised given counterevidence. In the present experiments, we demonstrate that 4- to 6-year-old children can revise their most fundamental beliefs in the physical domain (Experiment 1) and the psychological domain (Experiment 2) when they observe multiple pieces of belief-violating evidence.

Revising Core Beliefs in Young Children

Grapheme-color synesthetes experience linguistic symbols as having a consistent color (e.g., “The letter R is burgundy.”). Intriguingly, certain letters tend to be associated with certain colors, and these biases are not random: numerous properties of letters influence which letter is associated with which color. These influences, called “Regulatory Factors” (RFs), each explain some fraction of the variation in observed associations. No comprehensive model of the influences on grapheme-color associations exists: RFs have only been measured in isolation, are not always operationalized consistently, and often make competing predictions that cannot be accounted for in a univariate model. Here, we describe a statistical framework that integrates the predictions of all RFs into a single model, and thus yields a unified account of their influence on grapheme-color associations. Our model also links these predictions to measurable properties of language, offering a window into the multifactorial contributions to letter representation in the brain.

A Unifying Model of Grapheme-Color Associations in Synesthetes and Controls

Much research into persistence focuses on methods to increase trying without distinguishing whether persistence is rational. However, expectations of effort efficiency suggest that reducing effort in the face of repeated failure is logical. We performed archival behavioral coding to propose exploration as a rational means to extend persistence as new information is gained and the possibility of success is maintained. Infants were presented with an impossible task and exploratory behavior was classified. Infants decreased effort with increased experience failing, but persisted for longer when using several exploratory strategies and exploring for proportionally longer. These results confirm that infants are sensitive to the utility of their actions, and that exploration offers a means to persist even in the face of failure.

Try smarter, not harder: Exploration and strategy diversity are related to infant persistence

The mind readily learns cue-outcome associations where an object predicts a specific outcome. Previous work suggested that when multiple objects associated with different outcomes were jointly presented , the mind made conjunctive predictions that represented the common property of the associated outcomes. Using attentional tracking measures, we provided more evidence for the weighted summation framework when the conjunctive predictions involved spatial locations (Experiment 1) or conceptual categories (Experiment 2). Then, we examined the reverse of conjunction, where participants were presented with a single object, which is a part of an object pair that was previously associated with an outcome (Experiment 3). Rather than making predictions based on mental operations such as subtraction, we found that participants’ predictions were purely based on previous associations. These results together demonstrated the robust tendency to make conjunctive predictions based on knowledge of cue-outcome associations.

Association knowledge guides conjunctive predictions in novel situations

Humans are able to make sense of extraordinarily abstract concepts in mathematics (e.g., negative numbers). What is the underlying representation of these concepts? Integers extend natural numbers by including zero and negative numbers. To study the mental representation of integers, we employed a number comparison task in an online context. We replicated the previously-reported distance effect, in that far comparisons were faster than near comparisons. Namely, we observed reliable distance effects for positive and negative comparisons, and critically, an inverse distance effect for mixed comparisons. We conclude that the mental representation of integers may align with a hypothesis proposing the mental number line for negative numbers mirrors the natural number line. Moreover, we conclude that web-based data collection is a promising tool for future numerical cognition research.

The mental representation of integers: Further evidence for the negative number line as a reflection of the natural number line

In categorization tasks optimization of performance depends on attention to relevant stimulus features. However, studies show that adults and children seem to use different strategies when learning new categories. Deng & Sloutsky (2016) found that adults attend selectively, whereas children prefer to attend diffusely, even when the stimuli possess deterministic features (i.e. with 100% probability of belonging to a certain category). Most studies of attention in category learning rely on behavioral effects to infer attentional strategy, despite the availability of eye-tracking technology. In this study, we combine the use of category training and transfer paradigms (see Miles & Minda, 2009 and Deng & Sloutsky, 2016) and eye-tracking methods to investigate attentional strategies of children and adults during category learning. Preliminary results of our adult pilot (N = 14) confirm the prediction that adults optimize performance by attending increasingly to deterministic features of the stimulus once the categorical rule is found.

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Structural Comparisons of Noun and Verb Networks in the Mental Lexicon

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