What is it about?
Most theories of how people learn new concepts start with fixed descriptions of the objects to be categorized. By contrast, people often create new object descriptions to help them learn needed categories. To study how people generate new perceptual interpretations while they are learning new concepts, we built a computational model that solves Bongard Problems in a human-like way. In a Bongard Problem, 6 or so scenes belong to one category and another 6 scenes belong to another category, and a creative problem solver must come up with a rule that perfectly sorts the scenes into the two categories.
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Why is it important?
Our computational model presents a rigorous, publicly testable theory for an often neglected capacity of human creativity – our ability to create new descriptions for situations. This mode of creative thought characterizes scientific reasoning such as John Snow figuring out in 1854 that whether a Londoner contracted Cholera was determined by whether they got their water from a particular, contaminated pump, or James Maxwell developing a conception of gas pressure grounded in invisible gas molecules colliding against a container wall. Major innovations in science, mathematics, music, and art often involve constructing radically new descriptions. Our model shows the cognitive importance of building descriptions for a scene that depend on: the descriptions being simultaneously developed for other scenes, our ability to mentally simulate physical events, and emerging rules that we construct to structure our world.
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This page is a summary of: Perception and simulation during concept learning., Psychological Review, July 2023, American Psychological Association (APA),
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