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1. When generic language does not promote psychological essentialism.

   Vasilyeva, N.; Gopnik, A.; Lombrozo, T. (January 2020, Proceedings of the 42nd Annual Conference of the Cognitive Science Society)

   Denison, Stephanie; Mack, Michael; Xu, Yang; Armstrong, Blair C. (Ed.)

   Generic language (e.g., “Women are nurturing”; “Women do not like math”) is prominent in child-directed speech, and has been shown to promote essentialist beliefs about the relevant kind, supporting stereotyping and prejudice. Here we investigate a theoretically-motivated intervention to break the link between generics and essentialist assumptions. In a study with 223 3-8-year-old children who learned about novel social groups from generic language, we demonstrate that a structural construal of generics (attributing the category-property association to stable external constraints) mitigates essentialist assumptions about social categories. We discuss practical applications for reducing stereotype endorsement, and theoretical implications regarding the meaning of generic language and the development of social kind representations. 

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2. The Scope of Generic Generalizations: Developmental Changes in Judgments about Contextually-Restricted Generics

   Ritchie, Katherine; Curiel, Alejandro; Zhu, Tiffany; Pederneschi, Anna; Vasil, Ny (August 2025, Proceedings of the Annual Meeting of the Cognitive Science Society)

   Barner, David; Bramley, Neil; Ruggeri, Azzurra; Walker, Caren (Ed.)

   Generalizations are powerful tools to convey information agents need to predict and control their environments. However, some generalizations are restricted to “sociocultural bubbles”. How are such patterns communicated? We report one interdisciplinary study — bridging philosophy, linguistics, and cognitive developmental psychology — which examined the developing capacity for contextual restriction of generics in 4- 7-year-olds (N=137) and adults (N=63). We provided context cues signaling that the speaker used a generic generalization to convey a broad vs. contextually-restricted regularity, and measured endorsement of generics attributing properties prevalent globally vs. within “bubbles”. Adults endorsed generics flexibly, tracking context cues, but younger children struggled, over-attributing socially contingent properties to the group beyond the “bubble”, on par with context-general regularities. This reveals a troubling discrepancy between children and adults’ interpretations of generics, opening the door for cross-generational miscommunication. We discuss strategies to mitigate this in educational and family communication settings. 

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3. When Shall I Estimate Your Intent? Costs and Benefits of Intent Inference in Multi-Agent Interactions

   https://doi.org/10.23919/ACC53348.2022.9867155  

   Amatya, Sunny; Ghimire, Mukesh; Ren, Yi; Xu, Zhe; Zhang, Wenlong (June 2022, 2022 American Control Conference (ACC))

   This paper addresses incomplete-information dynamic games, where reward parameters of agents are private. Previous studies have shown that online belief update is necessary for deriving equilibrial policies of such games, especially for high-risk games such as vehicle interactions. However, updating beliefs in real time is computationally expensive as it requires continuous computation of Nash equilibria of the sub-games starting from the current states. In this paper, we consider the triggering mechanism of belief update as a policy defined on the agents’ physical and belief states, and propose learning this policy through reinforcement learning (RL). Using a two-vehicle uncontrolled intersection case, we show that intermittent belief update via RL is sufficient for safe interactions, reducing the computation cost of updates by 59% when agents have full observations of physical states. Simulation results also show that the belief update frequency will increase as noise becomes more significant in measurements of the vehicle positions. 

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4. Beta Probabilistic Databases: A Scalable Approach to Belief Updating and Parameter Learning

   https://doi.org/10.1145/3035918.3064026  

   Meneghetti, Niccolo'; Kennedy, Oliver; Gatterbauer, Wolfgang (January 2017, Proceedings of the 2017 ACM International Conference on Management of Data)

   Tuple-independent probabilistic databases (TI-PDBs) han- dle uncertainty by annotating each tuple with a probability parameter; when the user submits a query, the database de- rives the marginal probabilities of each output-tuple, assum- ing input-tuples are statistically independent. While query processing in TI-PDBs has been studied extensively, limited research has been dedicated to the problems of updating or deriving the parameters from observations of query results . Addressing this problem is the main focus of this paper. We introduce Beta Probabilistic Databases (B-PDBs), a general- ization of TI-PDBs designed to support both (i) belief updat- ing and (ii) parameter learning in a principled and scalable way. The key idea of B-PDBs is to treat each parameter as a latent, Beta-distributed random variable. We show how this simple expedient enables both belief updating and pa- rameter learning in a principled way, without imposing any burden on regular query processing. We use this model to provide the following key contributions: (i) we show how to scalably compute the posterior densities of the parameters given new evidence; (ii) we study the complexity of perform- ing Bayesian belief updates, devising efficient algorithms for tractable classes of queries; (iii) we propose a soft-EM algo- rithm for computing maximum-likelihood estimates of the parameters; (iv) we show how to embed the proposed algo- rithms into a standard relational engine; (v) we support our conclusions with extensive experimental results. 

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5. Contextual Restriction and Faultless Disagreement about Generics across Development

   Vasil, Ny; Campos, Gaia; Rouzbehani, Bahar; Curiel, Alejandro; Caoile, Jason; Khurelkhuu, Suren; Ritchie, Katherine (August 2025, Proceedings of the Annual Meeting of the Cognitive Science Society)

   Barner, David; Bramley, Neil; Ruggeri, Azzurra; Walker, Caren (Ed.)

   We report a study examining developmental changes in perceptions of disagreements among speakers who use generics to describe contextually-restricted or unrestricted regularities. Participants (65 adults and 222 5-12-year-olds) reacted to generic claims from two speakers who attributed ostensibly contradictory properties to a biological kind (e.g. “Xs are striped” and “Xs are spotted”). Crucially, we manipulated the scope of each speaker’s claim, or its contextual restriction: whether they made a claim restricted to a specific context (island habitat), or an unrestricted claim. Participants were asked whether the speakers could “both be right” (faultless disagreement rating). Adults were sensitive to contextual restriction: they allowed for faultless disagreement when contextual restrictions mis-aligned (with additional differentiation among experimental conditions described below), and denied it when both speakers restricted to the same context. Young children demonstrated striking partial competence in faultless disagreement judgments much earlier than prior developmental literature suggested; however, their response pattern was not quite adult-like. This is the first study to document faultless disagreement between differentially restricted generics, both in adults and in children, and to start mapping developmental changes in this capacity. We discuss the developmental trajectory, and implications for social functioning and learning, and draw connections to semantic theories. 

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