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Paper Iacopini2018 #
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We introduce a model for the emergence of innovations, in which cognitive processes are described as random walks on the network of links among ideas or concepts, and an innovation corresponds to the first visit of a node.

Whenever a random walker traverses an edges, the edge weight increases by δw.

The quantity δw, called reinforcement, is the only tun- able parameter of the model.

Used small-world network as the underlying space. Why?

scientific concept network from abstracts -> network -> with a certain parameter, it reproduces the Heaps' law exponent.

What's the relationship between the δw, network structure, and the Heaps exponent?

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