The Asymptotic Cost of Complexity

Martin W Cripps

Papers from arXiv.org

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.

Date: 2024-08
New Economics Papers: this item is included in nep-ipr and nep-mic
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