Infants' use of contextual cues in the generalization of effective actions from imitation.

We examined infants' ability to generalize effective actions in an imitation task. In Experiment 1, 15-month-olds imitated effective and ineffective actions on two similarly designed toys. They were then shown a third toy of the same design with both actions available. Children reliably touched and manipulated the effective action handle first and more persistently. In Experiment 2, however, 15-month-olds did not generalize the efficacy of the action when the test toy was different from the two demonstration toys. Experiment 3 replicated the findings of Experiment 2 but also showed that infants generalized efficacy when the demonstration toys differed from one another as well as from the test toy. Our findings are consistent with a computational model that uses certain rational pedagogical assumptions. Overall, the results suggest that 15-month-olds are sensitive to the sampling information they observe and use this information to guide whether to generalize efficacy information they learn from imitation.

Speaker reliability in preschoolers' inferences about the meanings of novel words.

Preschoolers participated in a modified version of the disambiguation task, designed to test whether the pragmatic environment generated by a reliable or unreliable speaker affected how children interpreted novel labels. Two objects were visible to children, while a third was only visible to the speaker (a fact known by the child). Manipulating whether a novel object was visible to both interlocutors or hidden from the child tested the child's understanding of pragmatic expectations of interlocutor competence. When interacting with a speaker with a history of accurately labeling familiar objects, children responded appropriately in both cases. When interacting with a speaker who previously generated inaccurate labels for familiar objects, children's behavior and eye-movements reflected their belief that the speaker was not a competent communicator. These data support the hypothesis that children consider the pragmatic environment constructed by an interlocutor when that speaker asks them to make a lexical inference.

Mechanism-based causal reasoning in young children.

The hypothesis that children develop an understanding of causal mechanisms was tested across 3 experiments. In Experiment 1 (N = 48), preschoolers had to choose as efficacious either a cause that had worked in the past, but was now disconnected from its effect, or a cause that had failed to work previously, but was now connected. Four-year-olds chose the now-connected cause more often than 3-year-olds. Experiment 2 (N = 16) showed 4-year-olds responded appropriately to an irrelevant modification in the same causal system. Experiment 3 (N = 24) demonstrated when the mechanism was batteries rather than connection, 3-year-olds could properly distinguish between relevant and irrelevant modifications. Together, these data suggest that understanding of specific causal mechanisms develops at different ages.

Edge replacement and minimality as models of causal inference in children.

Recently, much research has focused on causal graphical models (CGMs) as a computational-level description of how children represent cause and effect. While this research program has shown promise, there are aspects of causal reasoning that CGMs have difficulty accommodating. We propose a new formalism that amends CGMs. This edge replacement grammar formalizes one existing and one novel theoretical commitment. The existing idea is that children are determinists, in the sense that they believe that apparent randomness comes from hidden complexity, rather than inherent nondeterminism in the world. The new idea is that children think of causation as a branching process: causal relations grow not directly from the cause, but from existing relations between the cause and other effects. We have shown elsewhere that these two commitments together, when formalized, can explain and quantitatively fit the otherwise puzzling effect of nonindependence observed in the adult causal reasoning literature. We then test the qualitative predictions of this new formalism on children in a series of three experiments.

Children's developing understanding of the relation between variable causal efficacy and mechanistic complexity.

Two experiments investigated 3-4-year-olds' ability to infer the causal mechanisms for a pair of lights. In both experiments the exterior of the two lights appeared identical. In Experiment 1, one light displayed a stable activation pattern of a single color while the other light displayed a variable pattern of activation by cycling through a series of different colors (i.e., a more varied effect). Children were asked to judge which light had a more complex internal structure. Four-year-olds were more likely to match the light with the more variable effect with a more complex internal mechanism and the light with the more stable effect with a less complex mechanism. Three-year-olds' responses were at chance. Experiment 2 replicated this finding when the activation patterns of the two lights were described verbally but never demonstrated. Taken together, these results suggest that 4-year-olds appreciate that the variability of an object's causal efficacy is related to the complexity of its internal mechanistic structure.

Interactions between causal models, theories, and social cognitive development.

We propose a model of social cognitive development based not on a single modeling framework or the hypothesis that a single model accounts for children's developing social cognition. Rather, we advocate a Causal Model approach (cf. Waldmann, 1996), in which models of social cognitive development take the same position as theories of social cognitive development, in that they generate novel empirical hypotheses. We describe this approach and present three examples across various aspects of social cognitive development. Our first example focuses on children's understanding of pretense and involves only considering assumptions made by a computational framework. The second example focuses on children's learning from "testimony". It uses a modeling framework based on Markov random fields as a computational description of a set of empirical phenomena, and then tests a prediction of that description. The third example considers infants' generalization of action learned from imitation. Here, we use a modified version of the Rational Model of Categorization to explain children's inferences. Taken together, these examples suggest that research in social cognitive development can be assisted by considering how computational modeling can lead researchers towards testing novel hypotheses.