The Asymptotic Cost of Complexity

Published 27 Aug 2024 in econ.TH, cs.IT, and math.IT | (2408.14949v1)

Abstract: We propose a measure of learning efficiency for non-finite state spaces. We characterize the complexity of a learning problem by the metric entropy of its state space. We then describe how learning efficiency is determined by this measure of complexity. This is, then, applied to two models where agents learn high-dimensional states.

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Martin W Cripps

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