This reflects the intuition that people are bounded yet blessed with a capacity not just to learn from others, but to extend and repurpose existing knowledge to create new and more powerful ideas. Newton gave a famous answer to this question: “If I have seen further, it is by standing on the shoulders of giants” 23. How are people able to create and grasp such complex concepts that seem so far beyond their reach? On the other hand, these bounded reasoners can develop richly structured conceptual systems 16, 17, 18, produce sophisticated explanations 19, 20, 21 and push forward complex scientific theories 22. On the one hand, there is abundant evidence that people are bounded reasoners 1, 2, 3, 4, 5, entertain a rather small set of mental options at a time 6, 7, 8, 9, 10 and generally deviate from exhaustive search over large hypothesis spaces 11, 12, 13, 14, 15. People have a remarkable ability to develop rich and complex concepts despite limited cognitive capacities. ![]() Taken together, this work offers a computational account of how past experiences shape future conceptual discoveries and showcases the importance of curriculum design in human inductive concept inferences. Across four behavioural experiments (total n = 570), we demonstrate strong curriculum-order and conceptual garden-pathing effects that closely resemble our model predictions and differ from those of alternative accounts. This model predicts systematically different learned concepts when the same evidence is processed in different orders, without any extra assumptions about previous beliefs or background knowledge. This model uses a dynamic conceptual repertoire that can cache and later reuse elements of earlier insights in principled ways, modelling learning as a series of compositional generalizations. Here we present a computational model of conceptual bootstrapping. Such an ability to bootstrap enables us to grow rich mental concepts despite limited cognitive resources. ![]() To tackle a hard problem, it is often wise to reuse and recombine existing knowledge.
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