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Description: How do children explore in situations where exhaustive search is infeasible and not all options can be experienced? We study how 6- and 8-year-olds search for rewards in an explore-exploit task with spatially-correlated rewards. By combining behavioral data with a computational model that decomposes search into similarity-based generalization, uncertainty-directed exploration, and random exploration, we map out developmental trajectories of generalization and exploration. The behavioral data show strong and systematic differences between 6- and 8-year-olds in their capability to exploit environmental structure, with performance and adaptiveness of sampling decisions increasing with age. Through model-based analyses we disentangle different forms of exploration, finding signatures of both uncertainty-directed and random exploration in 6- and 8-year olds. The amount of random exploration strongly decreases as children get older, supporting the notion of a developmental "cooling off" process that modulates the randomness in sampling. However, importantly, children do not solely rely on random exploration, but actively seek out options with high uncertainty in a goal-directed fashion, and use inductive inferences to generalize from their experience to novel options. Our findings provide critical insights into the behavioral and computational principles underlying the developmental trajectory in exploration.

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