Baker, Chris

Bloom, Paul

Fawcett, Christine

Gelman, Susan

Goodman, Noah

Griffiths, Thomas L.

Hamlin, Kiley

Kushnir, Tamar

Lucas, Chris

Spelke, Elizabeth

Tenenbaum, Joshua

Ullman, Tomer

Wellman, Henry

Wynn, Karen

Xu, Fei

eScholarship - University of California

UC MercedProceedings of the Annual Meeting of the Cognitive Science SocietyTitleDevelopmental and computational perspectives on infant social cognitionPermalinkhttps://escholarship.org/uc/item/2x85p7wqJournalProceedings of the Annual Meeting of the Cognitive Science Society, 32(32)ISSN1069-7977AuthorsGoodman, NoahBaker, ChrisTenenbaum, Joshuaet al.Publication Date2010 Peer reviewedeScholarship.org Powered by the California Digital LibraryUniversity of CaliforniaDevelopmental and computational perspectives on infant social cognitionNoah D. Goodman (ndg@mit.edu)Chris L. Baker (clbaker@mit.edu)Tomer D. Ullman (tomeru@mit.edu)Joshua B. Tenenbaum (jbt@mit.edu)Department of Brain and Cognitive SciencesMassachusetts Institute of TechnologyKiley Hamlin (kiley.hamlin@yale.edu)Karen Wynn (karen.wynn@yale.edu)Paul Bloom (paul.bloom@yale.edu)Department of PsychologyYale UniversityChris G. Lucas (clucas@berkeley.edu)Thomas L. Griffiths (tom griffiths@berkeley.edu)Fei Xu (fei xu@berkeley.edu)Department of PsychologyUniversity of California, BerkeleyChristine Fawcett (christine.fawcett@mpi.nl)Max Planck Institute for PsycholinguisticsTamar Kushnir (tk397@cornell.edu)Department of PsychologyCornell UniversityHenry Wellman (hmw@umich.edu)Susan Gelman (gelman@umich.edu)Department of PsychologyUniversity of MichiganElizabeth Spelke (spelke@wjh.harvard.edu)Department of PsychologyHarvard UniversityKeywords: Social cognition; Cognitive Development;Computational Modeling; Theory of MindAdults effortlessly and automatically infer complex pat-terns of goals, beliefs, and other mental states as the causesof others’ actions. Yet before the last decade little was knownabout the developmental origins of these abilities in earlyinfancy. Our understanding of infant social cognition hasnow improved dramatically: even preverbal infants appearto perceive goals, preferences (Kushnir, Xu, & Wellman, inpress), and even beliefs from sparse observations of inten-tional agents’ behavior. Furthermore, they use these infer-ences to predict others’ behavior in novel contexts and tomake social evaluations (Hamlin, Wynn, & Bloom, 2007).Inspired by this work, computational modelers have inthe last few years begun to formalize the knowledge andinference mechanisms underlying infants’ social reasoning(Baker, Saxe, & Tenenbaum, 2009; Lucas, Griffiths, Xu, &Fawcett, 2009; Ullman et al., 2010). Many of these modelsshare deep similarities, explaining social inference in termsof an intuitive understanding of how an agent chooses amongactions. For instance, the principle of rational action, sug-gested in seminal work on infant social cognition (Gergely,Nádasdy, Csibra, & Biró, 1995), states that agents will selectthe best action to achieve their goals, given the constraints oftheir environment – or in a more sophisticated version, giventheir beliefs about the environment. This principle has beenformalized using notions of planning and decision-makingfrom economics and computer science. It underlies modelsthat make accurate quantitative predictions of the social in-ferences of adults and young children in a variety of experi-mental tests.The goal of this symposium will be to bring together de-velopmental psychologists and computational modelers in adialogue on the social inferences made by young infants,the mechanisms by which these inferences work and becomemore sophisticated in older children. The first talk of the sym-posium (Baker et. al) will briefly survey now-classic work oninfants’ understanding of goals and beliefs, and will intro-duce a general computational framework for modeling thesesocial inferences based on intuitive principles of rational ac-tion. Next will be two pairs of developmental and compu-tational talks, focusing on recent advances where there hasbeen important exchange between empirical work and mod-els. Kushnir, et al, and Lucas, et al, will describe work onunderstanding of others’ preferences. Hamlin, et al, and Ull-man, et al, will describe attribution of “prosocial” goals (suchas helping). The symposium will conclude with a discussionled by Spelke, highlighting gaps in our understanding of in-fant social cognition, areas where more computational workis needed, and where computational ideas might suggest newareas for developmental experiments.Close interaction and collaboration between developmen-talists and computational modelers studying infant social cog-nition is a fairly recent trend, yet it has already proven fruitful,as the talks in this symposium hope to demonstrate. Previ-ously, the research to be presented here has been discussedprimarily at conferences on computational modeling (e.g.,NIPS) or developmental psychology (e.g., the Cognitive De-velopment Society), or in small workshops bringing togethermodelers and experimentalists. The Cognitive Science Con-ference would be an ideal venue for a broad symposium onthis emerging, interdisciplinary subfield, due to its tradition ofbringing together theorists and experimentalists from a broadarray of disciplines. We expect the symposium will inter-est a wide audience and lead to new research directions andcollaborations engaging different segments of the CognitiveScience audience.Probabilistic models of belief-desire psychologyBaker, Goodman & Tenenbaum We propose a computational1184framework for modeling how humans interpret intentional ac-tions in terms of the mental states that cause behavior: chiefly,beliefs and desires. The framework represents a schema forintentional action using rational models of belief- and goal-based planning from economics and computer science knownas partially observable Markov decision problems. Agents’beliefs and desires are inferred by inverting this model ofrational planning using Bayesian inference, integrating thelikelihood of the observed actions with the prior over men-tal states. This approach formalizes in precise probabilisticterms the essence of previous qualitative approaches to in-fant action understanding, (e.g. Gergely et al., 1995). Wewill present results showing that our models account for in-fants’ and adults’ social judgments from a body of experi-ments, from simple inferences about goals, to joint inferencesof preferences and beliefs. We will also consider how a set ofalternative, heuristic-based models compare to our account.Young children use statistical sampling to infer the pref-erences of othersKushnir, Wellman & Gelman Psychological scientists usestatistical information to determine the workings of fellowhumans. We argue so do young children. In a few years,children progress from viewing human actions as intentionaland goal-directed to reasoning about the psychological causesunderlying such actions. Here we show that preschoolersand 20-month-old infants can use statistical information –namely, a violation of random sampling – to infer that anagent is expressing a preference for one object over another.Children saw a person remove 5 items of one type from acontainer of objects. Preschoolers and infants only inferred apreference for that type of object when there was a mismatchbetween the sample and population. Mere outcome consis-tency, time spent with and positive attention toward the ob-jects did not lead children to infer a preference. The findingsprovide an important demonstration of how statistical learn-ing could underpin the rapid acquisition of early psychologi-cal knowledge.A rational model of preference learning and choice pre-diction by childrenLucas, Griffiths, Xu & Fawcett We present a rational modelof preference learning that explains the behavior of childrenin several recent experiments, as well as a developmental shiftin which children come to understand that people have dis-tinct preferences. We first show that a simple econometricmodel can account for young children’s use of statistical in-formation in inferring preferences and their ability to general-ize others’ preferences from one category to another. We thenconsider the question of how children begin to treat other in-dividuals as having preferences that can differ from their own,showing that such a transition is consistent with Bayesian in-ference, given a model in which all people share preferencesand one in which preference can vary as possibilities. Finally,we discuss novel predictions made by our model concerningpreference understanding and the developmental shift.The enemy of my enemy is my friend: Infants interpretsocial behaviors in contextHamlin, Wynn & Bloom Recent research suggests thatyoung infants prefer prosocial to antisocial individu-als (Hamlin et al., 2007). While a preference for those whohelp others is certainly adaptive, there are potentially situa-tions in which unhelpful behavior is more appropriate (e.g.punishing others for their wrongdoing) or more socially diag-nostic (e.g. “The enemy of my enemy is my friend,” Aronson& Cope, 1968). This talk examines whether infants alwaysprefer those who are prosocial, in contexts in which antiso-cial behavior could be seen as punishment, or in which anindividual’s antisocial behavior may be an indication that heor she shares a negative opinion toward a disfavored other.Results suggest that even in the first year of life, infants eval-uate behaviors not only in terms of their valence, but also interms of certain qualities of their recipients.Help or hinder: Models of social goal inferenceUllman, Baker, Goodman & Tenenbaum Everyday social in-teractions are heavily influenced by our snap judgments aboutothers’ goals. Even young infants can infer the goals of inten-tional agents from observing how they interact with objectsand other agents in their environment: e.g., that one agentis ‘helping’ or ‘hindering’ another’s attempt to get up a hillor open a box. We propose a model for how people can in-fer these social goals from actions, based on inverse planningin multiagent Markov decision problems. The model infersthe goal most likely to be driving an agent’s behavior by as-suming the agent acts approximately rationally given envi-ronmental constraints and its model of other agents present.We also present behavioral evidence in support of this modelover a simpler, perceptual cue-based alternative.Discussion: Open challenges and future directionsSpelke The closing discussion will draw out gaps in ourcurrent understanding of infant social cognition, areas wheremore computational work is needed, and places where com-putational ideas might suggest new areas for developmentalexperiments.ReferencesAronson, E., & Cope, V. (1968). My enemy’s enemy is my friend.Journal of Personality and Social Psychology, 8, 8–12.Baker, C. L., Saxe, R., & Tenenbaum, J. B. (2009). Action under-standing as inverse planning. Cognition, 113, 329-349.Gergely, G., Nádasdy, Z., Csibra, G., & Biró, S. (1995). Taking theintentional stance at 12 months of age. Cognition, 56, 165–193.Hamlin, J. K., Wynn, K., & Bloom, P. (2007). Social evaluation bypreverbal infants. Nature, 450, 557–560.Kushnir, T., Xu, F., & Wellman, H. (in press). Young children usestatistical sampling to infer the preferences of others. Psycholog-ical Science.Lucas, C., Griffiths, T. L., Xu, F., & Fawcett, C. (2009). A rationalmodel of preference learning and choice prediction by children.Advances in Neural Information Processing Systems (NIPS) 21.Ullman, T., Baker, C., Macindoe, O., Evans, O., Goodman, N., &Tenenbaum, J. (2010). Help or hinder: Bayesian models of so-cial goal inference. Advances in Neural Information ProcessingSystems (NIPS) 22.1185

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Developmental and computational perspectives on infant social cognition

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Developmental and computational perspectives on infant social cognition

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