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We investigate how humans leverage sparse observations of social interaction to infer the rich internal structure of human social collectives. We propose a computational model of this process which integrates a domain-general structure learning mechanism with domain-specific knowledge about social contexts (i.e.: “intuitive sociologies”). We test our model in two experiments where participants observe a sequence of animated interactions between agents, and then assign the agents to groups according to their role or type within the social collective. Crucially, the two experiments depict different types of social interactions which reflect different types of underlying social structures. The patterns of correspondence between model predictions and human data support our account, and demonstrate the importance of both general statistical learning and specific social knowledge when reasoning about social collectives. Keywords: Social Inference; Intergroup Cognition; Computational Modeling

CogSci 2022

Inferring the internal structure of social collectives

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**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.

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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.

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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.
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<br>[**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)
<br>[**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. 





Intuitively, adding uninformed individuals to a group should undermine group efficiency, as they create coordination costs while lacking the expertise to meaningfully contribute. However, uninformed individuals may be able to overcome deadlocks in otherwise polarized groups by heightening conformity pressures. Modeling group members’ decision making using a sequential sampling model based on Decision Field Theory (DFT: Busemeyer & Townsend, 1993), we present an existence proof of how ignorance can, in contrast to intuition and prominent economic accounts, facilitate improved group decision making. The implications of these findings for cognitive science, organizational behavior, and social impact are discussed.

In the Dark: Agent-Based Modeling of Uninformed Individuals within Polarized Groups

Diversity of social identities can improve the performance of groups through varied cognitive and communicative pathways. Recently, research efforts have focused on identifying when we should expect to see these potential benefits in real-world settings. While most research to date has studied this topic at individual and interpersonal levels, in this paper, we develop an agent-based model to explore how various aspects of homophily, the tendency of individuals to associate with similar others, affects performance at a larger scale. Study 1 examines how two types of homophily---identity-driven and opinion-driven---impact collective performance on a sequential decision-making task via modulating network formation and trust relations. Study 2 considers how the presence of identity-based conformity pressure can affect the findings from the first study. Overall, we find that the effect of homophily on performance is complex, depending on the operative dimensions of similarity, mediating pathways, and the specific outcome of interest. Finally, we discuss the implications of our results for policy interventions aiming to improve group performance.

Diversity and homophily in social networks

Behavioural cascades through social reinforcement are ubiquitous in human and animal groups. Nonetheless, we only have a rudimentary understanding of which choices are more likely to initiate cascades. Here we investigate the role of response time (RT) asymmetries (i.e., one choice alternative being selected faster than the other) in shaping behavioural cascades by combining an empirical and modelling approach. RT asymmetries are found in a wide range of decision-making contexts, including police shooting, risky choice, and memory retrieval. How they shape collective dynamics, is, however, unknown. Applying evidence accumulation models to analyse behaviour in a sequential choice paradigm, we show that RT asymmetries crucially shape behavioural cascades. Using simulations, we show that especially start point biases (and to a less extent varying drift rates) can initiate cascades, as they lead to rapid choices for one choice alternative. Our results highlight the importance of RT asymmetries in shaping collective dynamics.

How the cognitive mechanisms underlying fast choices influence information spread and response bias amplification in groups

Children do not learn language from passively analyzing correlations between language and observations, but from interaction with caregivers or peers. The non-nativist approach claims that the main driver of language learning should be to achieve communicative goals. Imitation, on the other hand, is another natural desire that many argue influences language learning. However, there are still gaps in the research on what roles communicative goals and imitating linguistic input play in language acquisition, due to the difficulty of performing comprehensive experiments with human learners. In this paper, we propose a computational framework using simulated experiments that allows us to compare the roles of the two drivers. Specifically, we simulate a two-way communication game between a speaker, corresponding to a language learner, and a listener, corresponding to a caregiver or teacher. The speaker's communicative goals are modeled as rewards for successful completion of a referential game, and imitation is performed by mimicking feedback from the listener. The listener adaptively chooses to give feedback and makes choices based on the speaker's utterances. 

With empirical results on naturalistic visual and language data, we find that communicative goals play an important role in driving language learning, whereas imitation accelerates the learning process. We also find that (1) models trained with communicative goals tend to use minimal vocabulary and utterances and overextend them to concepts outside the original word meanings; (2) the strategy with which the listener provides feedback also influences the learning results and speed. Code and data for replicating the experiments are available\footnote{\url{https://bit.ly/interactgym}} to spur future research on models for computational studies of language learning.

Language Learning from Communicative Goals and Linguistic Input

Picture book reading is a common word-learning context from which parents repeatedly name objects to their child and it has been found to facilitate early word learning. To learn the correct word-object mappings in a book-reading context, infants need to be able to link what they see with what they hear. However, given multiple objects on every book page, it is not clear how infants direct their attention to objects named by parents. The aim of the current study is to examine how infants mechanistically discover the correct word-object mappings during book reading in real time. We used head-mounted eye-tracking during parent-infant picture book reading and measured the infant's moment-by-moment visual attention to the named referent. We also examined how gesture cues provided by both the child and the parent may influence infants' attention to the named target. We found that although parents provided many object labels during book reading, infants were not able to attend to the named objects easily. However, their abilities to follow and use gestures to direct the other social partner’s attention increase the chance of looking at the named target during parent naming.

Examining Real-time Attention Dynamics in Parent-infant Picture Book Reading

Children start to communicate and use language in social interactions from the very early stages in development. This allows them to experiment with their current linguistic knowledge and receive valuable feedback from their interlocutors. We conducted a large-scale corpus study to examine the quality of positive and negative Communicative Feedback signals that caregivers provide in terms of time-contingent responses and clarification requests. We found evidence for the effect of such feedback in supporting children’s production of intelligible speech.
The broad impact of this paper is to highlight how general social feedback mechanisms that govern human communication can also support child language acquisition.

Communicative Feedback as a Mechanism Supporting the Production of Intelligible Speech in Early Childhood

Do children learn language from the words that they produce themselves? Because children know that they have imperfect knowledge of language, they could simply ignore their own productions. However, children could also learn from their productions -- using what they say and how their caregivers respond to update their language models. Using irregular plurals as a case study, we conducted a large-scale corpus analysis and two experimental studies to understand the role of children's productions and caregivers' responses in language learning. We demonstrate that children do learn from their own production, with errorful utterances leading to more errors. However, at least in some contexts, children can use implicit corrections from parents to offset the negative effects of their errors. Children thus appear to learn not only from their caregivers' productions, but also from their own productions and from the relationship between the two.

Of mouses and mans: the role of production and feedback in language learning

According to cross-situational learning, infants aggregate statistical information across naming events to resolve ambiguous word-referent mappings. While lab experiments show that learners are sensitive to these statistics, in studies using naturalistic stimuli, adults often fail to infer the correct referent. Here, we examined how young learners' input “in the wild” differs from laboratory experiments. We analyzed the temporal and spatial regularities of parent naming events in a naturalistic dataset of parent-child play and tested their effect on infants' visual attention. Parents were less likely to name the same toy twice than to name two different toys in sequence, except at short lags (0>t>5s). Most of the visual scenes accompanying naming events were composed of several toys of approximately equal (small) size. Child-attention to the target toy appeared to be modulated primarily by size. These results underscore the importance of quantifying naturalistic statistical regularities for understanding the mechanisms of word learning.

Quantifying cross-situational statistics during parent-child toy play

Iconicity refers to a resemblance between word form and meaning. Previous work has shown that iconic words are learned earlier and processed faster. Here we examined whether iconicity would also affect a recognition memory task. We also manipulated the level at which items were encoded—with a focus on either their meaning or their form—in order to gain insight into the mechanism by which iconicity would affect memory. In comparison with non-iconic words, iconic words were associated with a higher false alarm rate, a lower d’ score, and a lower criterion C. We did not observe any interaction between iconicity and encoding condition. We also conducted an analysis of recognition memory megastudy data and found that iconicity was predictive of higher false alarms and a lower criterion C across 1,646 items. We interpret these results as suggesting that iconicity leads to a feeling of familiarity in recognition memory.

Effects of Iconicity in Recognition Memory

A hallmark of human memory is the ability to integrate discrete experiences into cognitive maps. A fundamental form of this integration is transitive inference (TI), in which overlapping premises (A < B, B < C) are integrated into a unified representation of a relational hierarchy (A < B < C). Few existing theories provide a mechanistic account of this construction of relational knowledge and how it is shaped by different training conditions. This study builds on recent findings that TI is facilitated by chaining of overlapping premises, with a new behavioral experiment confirming an advantage over non-overlapping sequences matched for premise frequency and spacing. A subsequent simulation study shows that the chaining effect is captured by a particle filter which performs approximate Bayesian inference about the latent hierarchy. These results provide a better understanding of how chaining shapes the construction of relational knowledge in the face of uncertainty and forgetting.

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In the Dark: Agent-Based Modeling of Uninformed Individuals within Polarized Groups

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