How do children and adults differ in their search for rewards? We considered three different hypotheses that attribute developmental differences to (a) children’s increased random sampling, (b) more directed exploration toward uncertain options, or (c) narrower generalization. Using a search task in which noisy rewards were spatially correlated on a grid, we compared the ability of 55 younger children (ages 7 and 8 years), 55 older children (ages 9–11 years), and 50 adults (ages 19–55 years) to successfully generalize about unobserved outcomes and balance the exploration–exploitation dilemma. Our results show that children explore more eagerly than adults but obtain lower rewards. We built a predictive model of search to disentangle the uni...
Item does not contain fulltextThe prevalence and reward-value of targets have an influence on visual...
In 2 experiments, the authors investigated age differences in memory search under 4 conditions: forw...
One of the greatest challenges for artificial intelligence is how to behave adaptively in scenarios ...
Are young children just random explorers who learn serendipitously? Or are even young children guide...
learning from past experiences helps orient the exploration of unknown environments. yet how we lear...
Making the best decision in a given situation requires a person to strike a unique balance between e...
In an experiment involving a total of 124 participants, divided into eight age groups (6-, 8-, 10-, ...
Three experiments investigated visual search for targets that differed from distractors in colour, s...
Abstract: Most studies of visual search across the life span have focused on classic feature and con...
What drives human search in situations with sparse rewards? We let preschoolers (age 24-52 months)pl...
This dissertation examines how decision-making strategies and exploration patterns change across the...
Most studies of visual search across the life span have focused on classic feature and conjunction s...
How do children and adults search for information when stepwise-optimal strategies fail to identify ...
Five- to 11-year-olds (N = 91) explored virtual environments with the goal of learning where everyth...
It is often unclear which course of action gives the best outcome. We can reduce this uncertainty by...
Item does not contain fulltextThe prevalence and reward-value of targets have an influence on visual...
In 2 experiments, the authors investigated age differences in memory search under 4 conditions: forw...
One of the greatest challenges for artificial intelligence is how to behave adaptively in scenarios ...
Are young children just random explorers who learn serendipitously? Or are even young children guide...
learning from past experiences helps orient the exploration of unknown environments. yet how we lear...
Making the best decision in a given situation requires a person to strike a unique balance between e...
In an experiment involving a total of 124 participants, divided into eight age groups (6-, 8-, 10-, ...
Three experiments investigated visual search for targets that differed from distractors in colour, s...
Abstract: Most studies of visual search across the life span have focused on classic feature and con...
What drives human search in situations with sparse rewards? We let preschoolers (age 24-52 months)pl...
This dissertation examines how decision-making strategies and exploration patterns change across the...
Most studies of visual search across the life span have focused on classic feature and conjunction s...
How do children and adults search for information when stepwise-optimal strategies fail to identify ...
Five- to 11-year-olds (N = 91) explored virtual environments with the goal of learning where everyth...
It is often unclear which course of action gives the best outcome. We can reduce this uncertainty by...
Item does not contain fulltextThe prevalence and reward-value of targets have an influence on visual...
In 2 experiments, the authors investigated age differences in memory search under 4 conditions: forw...
One of the greatest challenges for artificial intelligence is how to behave adaptively in scenarios ...