Iterated learning in populations of Bayesian agents

Abstract

Previous analytic results (Griffiths & Kalish, 2007) show that repeated learning and transmission of languages in populations of Bayesian learners results in distributions of languages which directly reflect the biases of learners. This result potentially has profound implications for our understanding of the link between the human language learning… (More)

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