When Learners Surpass their Sources: Mathematical Modeling of Learning from an Inconsistent Source

@article{Mandelshtam2014WhenLS,
  title={When Learners Surpass their Sources: Mathematical Modeling of Learning from an Inconsistent Source},
  author={Yelena Mandelshtam and Natalia Komarova},
  journal={Bulletin of mathematical biology},
  year={2014},
  volume={76 9},
  pages={2198-216}
}
It has been reported in the literature that both adults and children can, to a different degree, modify and regularize the often-inconsistent linguistic input they receive. We present a new algorithm to model and investigate the learning process of a learner mastering a set of (grammatical or lexical) forms from an inconsistent source. The algorithm is related to reinforcement learning and drift-diffusion models of decision making, and possesses several psychologically relevant properties such… CONTINUE READING
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