@article {4814, title = {Online Developmental Science to Foster Innovation, Access, and Impact}, journal = {Trends in Cognitive Sciences}, volume = {24}, year = {2020}, month = {09/2020}, pages = {675 - 678}, issn = {13646613}, doi = {10.1016/j.tics.2020.06.004}, url = {https://linkinghub.elsevier.com/retrieve/pii/S1364661320301455}, author = {Sheskin, Mark and Scott, Kimberly and Mills, Candice M. and Bergelson, Elika and Bonawitz, Elizabeth and Elizabeth S Spelke and Fei-Fei, Li and Keil, Frank C. and Gweon, Hyowon and Joshua B. Tenenbaum and Julian Jara-Ettinger and Adolph, Karen E. and Rhodes, Marjorie and Frank, Michael C. and Mehr, Samuel A. and Laura Schulz} } @article {3621, title = {Children understand that agents maximize expected utilities.}, journal = {Journal of Experimental Psychology: General}, volume = {146}, year = {2017}, month = {Jan-11-2017}, pages = {1574 - 1585}, abstract = {

A growing set of studies suggests that our ability to infer, and reason about, mental states is supported by the assumption that agents maximize utilities{\textemdash}the rewards they attain minus the costs they incur. This assumption enables observers to work backward from agents{\textquoteright} observed behavior to their underlying beliefs, preferences, and competencies. Intuitively, however, agents may have incomplete, uncertain, or wrong beliefs about what they want. More formally, agents try to maximize their expected utilities. This understanding is crucial when reasoning about others{\textquoteright} behavior: It dictates when actions reveal preferences, and it makes predictions about the stability of behavior over time. In a set of 7 experiments we show that 4- and 5-year-olds understand that agents try to maximize expected utilities, and that these responses cannot be explained by simpler accounts. In particular, these results suggest a modification to the standard belief/desire model of intuitive psychology. Children do not treat beliefs and desires as independent; rather, they recognize that agents have beliefs about their own desires and that this has consequences for the interpretation of agents{\textquoteright} actions.

}, issn = {0096-3445}, doi = {10.1037/xge0000345}, url = {http://doi.apa.org/getdoi.cfm?doi=10.1037/xge0000345http://psycnet.apa.org/journals/xge/146/11/1574.pdf}, author = {Julian Jara-Ettinger and Floyd, Samantha and Joshua B. Tenenbaum and Laura Schulz} } @article {2763, title = {Rational quantitative attribution of beliefs, desires, and percepts in human mentalizing}, journal = {Nature Human Behavior}, volume = {1}, year = {2017}, month = {03/2017}, abstract = {

Social cognition depends on our capacity for {\textquoteleft}mentalizing{\textquoteright}, or explaining an agent{\textquoteright}s behaviour in terms of their mental states. The development and neural substrates of mentalizing are well-studied, but its computational basis is only beginning to be probed. Here we present a model of core mentalizing computations: inferring jointly an actor{\textquoteright}s beliefs, desires and percepts from how they move in the local spatial environment. Our Bayesian theory of mind (BToM) model is based on probabilistically inverting artificial-intelligence approaches to rational planning and state estimation, which extend classical expected-utility agent models to sequential actions in complex, partially observable domains. The model accurately captures the quantitative mental-state judgements of human participants in two experiments, each varying multiple stimulus dimensions across a large number of stimuli. Comparative model fits with both simpler {\textquoteleft}lesioned{\textquoteright} BToM models and a family of simpler non-mentalistic motion features reveal the value contributed by each component of our model.

}, keywords = {Human behaviour, Social behaviour}, doi = {doi:10.1038/s41562-017-0064}, url = {http://www.nature.com/articles/s41562-017-0064}, author = {Chris Baker and Julian Jara-Ettinger and Rebecca Saxe and Joshua B. Tenenbaum} } @article {2595, title = {Mastery of the logic of natural numbers is not the result of mastery of counting: Evidence from late counters. }, journal = {Developmental Science}, year = {2016}, doi = {10.1111/desc.12459}, author = {Julian Jara-Ettinger and Steve Piantadosi and Elizabeth S Spelke and Roger Levy and Edward Gibson} } @article {2492, title = {The naive utility calculus: computational principles underlying social cognition}, journal = {Trends Cogn Sci.}, year = {2016}, doi = {10.1016/j.tics.2016.05.011}, url = {https://www.ncbi.nlm.nih.gov/pubmed/27388875}, author = {Julian Jara-Ettinger and Hyowon Gweon and Laura Schulz and Joshua B. Tenenbaum} } @article {1194, title = {Children{\textquoteright}s understanding of the costs and rewards underlying rational action}, journal = {Cognition}, volume = {140}, year = {2015}, month = {07/2015}, pages = {14{\textendash}23}, abstract = {

Humans explain and predict other agents{\textquoteright} behavior using mental state concepts, such as beliefs and desires. Computational and developmental evidence suggest that such inferences are enabled by a principle of rational action: the expectation that agents act efficiently, within situational constraints, to achieve their goals. Here we propose that the expectation of rational action is instantiated by a na{\"\i}ve utility calculus sensitive to both agent-constant and agent-specific aspects of costs and rewards associated with actions. In four experiments, we show that, given an agent{\textquoteright}s choices, children (range: 5-6 year olds; N=96) can infer unobservable aspects of costs (differences in agents{\textquoteright} competence) from information about subjective differences in rewards (differences in agents{\textquoteright} preferences) and vice versa. Moreover, children can design informative experiments on both objects and agents to infer unobservable constraints on agents{\textquoteright} actions.

}, doi = {10.1016/j.cognition.2015.03.006}, url = {http://www.sciencedirect.com/science/article/pii/S0010027715000566}, author = {Julian Jara-Ettinger and Hyowon Gweon and Joshua B. Tenenbaum and Laura Schulz} } @article {1206, title = {Not So Innocent: Toddlers{\textquoteright} Inferences About Costs and Culpability}, journal = {Psychological Science }, volume = {26}, year = {2015}, month = {05/2015}, pages = {633-40}, abstract = {

Adults{\textquoteright} social evaluations are influenced by their perception of other people{\textquoteright}s competence and motivation: Helping when it is difficult to help is praiseworthy, and not helping when it is easy to help is reprehensible. Here, we look at whether children{\textquoteright}s social evaluations are affected by the costs that agents incur. We found that toddlers can use the time and effort associated with goal-directed actions to distinguish agents, and that children prefer agents who incur fewer costs in completing a goal. When two agents refuse to help, children retain a preference for the more competent agent but infer that the less competent agent is nicer. These results suggest that children value agents who incur fewer costs, but understand that failure to engage in a low-cost action implies a lack of motivation. We propose that a naive utility calculus underlies inferences from the costs and rewards of goal-directed action and thereby supports social cognition.

}, keywords = {cognitive development, open data, open materials, social cognition, theory of mind}, doi = {10.1177/0956797615572806}, url = {http://pss.sagepub.com/content/early/2015/04/09/0956797615572806}, author = {Julian Jara-Ettinger}, editor = {Joshua B. Tenenbaum and Laura Schulz} }