Abstract:
This note discusses two challenges to simulating the social process of science. The first is developing an adequately rich representation of the underlying Data Generation Process which scientific progress can \"learn\". The second is how to get effective data on what, in broad terms, the properties of the \"future\" are. Paradoxically, with due care, we may learn a lot about the future by studying the past.
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