Developmental and computational perspectives on infant social cognition

Developmental and computational perspectives on infant social cognition Noah D. Goodman (ndg@mit.edu) Chris L. Baker (clbaker@mit.edu) Tomer D. Ullman (tomeru@mit.edu) Joshua B. Tenenbaum (jbt@mit.edu) Kiley Hamlin (kiley.hamlin@yale.edu) Karen Wynn (karen.wynn@yale.edu) Paul Bloom (paul.bloom@yale.edu) Department of Psychology Yale University Department of Brain and Cognitive Sciences Massachusetts Institute of Technology Chris G. Lucas (clucas@berkeley.edu) Thomas L. Griffiths (tom griffiths@berkeley.edu) Fei Xu (fei xu@berkeley.edu) Tamar Kushnir (tk397@cornell.edu) Department of Psychology University of California, Berkeley Henry Wellman (hmw@umich.edu) Susan Gelman (gelman@umich.edu) Christine Fawcett (christine.fawcett@mpi.nl) Department of Psychology University of Michigan Department of Psychology Cornell University Max Planck Institute for Psycholinguistics Elizabeth Spelke (spelke@wjh.harvard.edu) Department of Psychology Harvard University Keywords: Social cognition; Cognitive Development; Computational Modeling; Theory of Mind Adults effortlessly and automatically infer complex pat- terns of goals, beliefs, and other mental states as the causes of others’ actions. Yet before the last decade little was known about the developmental origins of these abilities in early infancy. Our understanding of infant social cognition has now improved dramatically: even preverbal infants appear to perceive goals, preferences (Kushnir, Xu, & Wellman, in press), 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 to make social evaluations (Hamlin, Wynn, & Bloom, 2007). Inspired by this work, computational modelers have in the last few years begun to formalize the knowledge and inference mechanisms underlying infants’ social reasoning (Baker, Saxe, & Tenenbaum, 2009; Lucas, Griffiths, Xu, & Fawcett, 2009; Ullman et al., 2010). Many of these models share deep similarities, explaining social inference in terms of an intuitive understanding of how an agent chooses among actions. For instance, the principle of rational action, sug- gested in seminal work on infant social cognition (Gergely, N´adasdy, Csibra, & Bir´o, 1995), states that agents will select the best action to achieve their goals, given the constraints of their environment – or in a more sophisticated version, given their beliefs about the environment. This principle has been formalized using notions of planning and decision-making from economics and computer science. It underlies models that 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 a dialogue on the social inferences made by young infants, the mechanisms by which these inferences work and become more sophisticated in older children. The first talk of the sym- posium (Baker et. al) will briefly survey now-classic work on infants’ understanding of goals and beliefs, and will intro- duce a general computational framework for modeling these social 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 has been important exchange between empirical work and mod- els. Kushnir, et al, and Lucas, et al, will describe work on understanding of others’ preferences. Hamlin, et al, and Ull- man, et al, will describe attribution of “prosocial” goals (such as helping). The symposium will conclude with a discussion led by Spelke, highlighting gaps in our understanding of in- fant social cognition, areas where more computational work is needed, and where computational ideas might suggest new areas 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 discussed primarily at conferences on computational modeling (e.g., NIPS) or developmental psychology (e.g., the Cognitive De- velopment Society), or in small workshops bringing together modelers and experimentalists. The Cognitive Science Con- ference would be an ideal venue for a broad symposium on this emerging, interdisciplinary subfield, due to its tradition of bringing together theorists and experimentalists from a broad array of disciplines. We expect the symposium will inter- est a wide audience and lead to new research directions and collaborations engaging different segments of the Cognitive Science audience. Probabilistic models of belief-desire psychology Baker, Goodman & Tenenbaum We propose a computational