# Learning in a Small/Big World

@article{Leung2020LearningIA, title={Learning in a Small/Big World}, author={Benson Tsz Kin Leung}, journal={ArXiv}, year={2020}, volume={abs/2009.11917} }

This paper looks into how learning behavior changes with the complexity of the inference problem and the individual's cognitive ability, as I compare the optimal learning behavior with bounded memory in small and big worlds. A learning problem is a small world if the state space is much smaller than the size of the bounded memory and is a big world otherwise. I show that first, optimal learning behavior is almost Bayesian in small worlds but is significantly different from Bayesian in big…

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