Children’s understanding of the costs and rewards underlying rational action

Jara‐Ettinger, Julian; Gweon, Hyowon; Tenenbaum, Joshua B.; Schulz, Laura

doi:10.1016/j.cognition.2015.03.006

Cited by 119 publications

(137 citation statements)

References 34 publications

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“…That is, teachers may act to increase learners’ perceived rewards and decrease their perceived costs. Recent work has formalized this intuition to suggest that people reason about their own and others’ goal‐directed actions via a naive utility calculus (Jara‐Ettinger et al., ), and a number of recent empirical studies shows that even young children reason about others’ actions in ways that are consistent with predictions of utility‐based models (e.g., Bridgers, et al., ; Jara‐Ettinger et al., ). The current work provides indirect support for the idea that children reason about expected rewards and costs.…”

Section: Discussionmentioning

confidence: 99%

From Exploration to Instruction: Children Learn From Exploration and Tailor Their Demonstrations to Observers’ Goals and Competence

Gweon

Schulz

2018

Child Development

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This study investigated whether children learn from exploration and act as effective informants by providing informative demonstrations tailored to observers' goals and competence. Children (4.0-6.9 years, N = 98) explored a causally ambiguous toy to discover its causal structure and then demonstrated the toy to a naive observer. Children provided more costly and informative evidence when the observer wanted to learn about the toy than observe its effects (Experiment 1) and when the observer was ordinary than exceptionally intelligent (Experiment 2). Relative to the evidence they generated during exploration, children produced fewer, less costly actions when the observer wanted or needed less evidence. Children understand the difference between acting-to-learn and acting-to-inform; after learning from exploration, they consider others' goals and competence to provide "uninstructed instruction".

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Section: Discussionmentioning

confidence: 99%

From Exploration to Instruction: Children Learn From Exploration and Tailor Their Demonstrations to Observers’ Goals and Competence

Gweon

Schulz

2018

Child Development

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“…Subsequent models have considerably extended this basic premise to capture causal relations between other kinds of mental states. For example: Greg’s choices additionally depend on (what he believes about) the costs of his actions [11]; his beliefs update in response to new evidence [7]; his actions are influenced by his habits [12]; and so on. A hierarchical Bayesian model of this intuitive causal theory can explain both observers’ forward inferences (predicting Greg’s actions given his beliefs and desires) and inverse inferences (inferring Greg’s beliefs and desires given his actions) [10].…”

Section: Situating Emotion Concepts Within An Intuitive Theory Of Mindmentioning

confidence: 99%

Formalizing emotion concepts within a Bayesian model of theory of mind

Saxe

Houlihan

2017

Current Opinion in Psychology

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Sensitivity to others’ emotions is foundational for many aspects of human life, yet computational models do not currently approach the sensitivity and specificity of human emotion knowledge. Perception of isolated physical expressions largely supplies ambiguous, low-dimensional, and noisy information about others' emotional states. By contrast, observers attribute specific granular emotions to another person based on inferences of how she interprets (or “appraises”) external events in relation to her other mental states (goals, beliefs, moral values, costs). These attributions share neural mechanisms with other reasoning about minds. Situating emotion concepts in a formal model of people's intuitive theories about other minds is necessary to effectively capture humans' fine-grained emotion understanding.

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“…In one series of experiments [57] we found that when five-year-olds learn an agent's costs and choices, they infer a reward function that guarantees that the agent maximized her utilities. We showed children a puppet who chooses crackers over cookies when both items are equidistant, but cookies over crackers when the cookies are closer (Figure 4a).…”

Section: Evidence For the Naïve Utility Calculusmentioning

confidence: 99%

The Naïve Utility Calculus: Computational Principles Underlying Commonsense Psychology

Jara‐Ettinger¹,

Gweon²,

Schulz³

et al. 2016

Trends in Cognitive Sciences

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We propose that human social cognition is structured around a basic understanding of ourselves and others as intuitive utility maximizers: From a young age, humans implicitly assume that agents choose goals and actions to maximize the rewards they expect to obtain relative to the costs they expect to incur. This "naïve utility calculus" lets both children and adults observe others' behavior and infer their beliefs and desires, their longer-term knowledge and preferences, and even their character: who is knowledgeable or competent, who is praiseworthy or blameworthy, who is friendly, indifferent or an enemy. We review studies providing support for the naïve utility calculus, and we show how it captures much of the rich social reasoning humans engage in from infancy. Commonsense PsychologyTheories of decision-making have been at the heart of psychology since the field's inception, but only recently has the field turned to the study of how humans -especially the youngest humansthink humans make decisions. When we watch someone make a choice, we explain it in terms of their goals, preferences, personalities, and moral beliefs. This capacity -our commonsense psychology -is the cognitive foundation of human society. It lets us share what we have and know, with those from whom we expect the same in return, and it guides how we evaluate those who deviate from our expectations.The representations and inferential power underlying commonsense psychology trace back to early childhood -before children begin kindergarten, and often even in infancy. Work on how children reason about other agents' goals [1][2][3][4][5][6][7][8], desires [9][10][11], beliefs [12][13][14][15][16][17][18], and pro-social behavior [19][20][21][22][23][24][25][26][27][28][29] has advanced our understanding of what in our commonsense psychology is at work in early infancy [30][31][32] and what develops [16][17][33][34][35]. Nonetheless, major theoretical questions remain unresolved. What computations underlie our commonsense psychology, and to what extent are they specific to the social domain? Are there a small number of general principles by which humans reason about and evaluate other agents, or do we instead learn a large number of special case rules and heuristics? To what extent is there continuity between the computations supporting commonsense psychology in infancy and later ages? Is children's social-cognitive development a progressive refinement of a computational system in place from birth, or are there fundamentally new computational principles coming into play?In this article we advance a hypothesis that offers answers to each of these questions, and provides a unifying framework in which to understand the diverse social-cognitive capacities we see even in young children. We propose that human beings, from early infancy, interpret others' intentional actions through the lens of a naïve utility calculus: that is, people assume that others choose actions to maximize utilities -the rewards they expect to obtain relative to the costs...

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Children’s understanding of the costs and rewards underlying rational action

Cited by 119 publications

References 34 publications

From Exploration to Instruction: Children Learn From Exploration and Tailor Their Demonstrations to Observers’ Goals and Competence

From Exploration to Instruction: Children Learn From Exploration and Tailor Their Demonstrations to Observers’ Goals and Competence

Formalizing emotion concepts within a Bayesian model of theory of mind

The Naïve Utility Calculus: Computational Principles Underlying Commonsense Psychology

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