Focused learning promotes continual task performance in humans

@article{Flesch2018FocusedLP,
  title={Focused learning promotes continual task performance in humans},
  author={Timo Flesch and Jan Balaguer and Ronald Dekker and Hamed Nili and Christopher Summerfield},
  journal={bioRxiv},
  year={2018}
}
Humans can learn to perform multiple tasks in succession over the lifespan (“continual” learning), whereas current machine learning systems fail. Here, we investigated the cognitive mechanisms that permit successful continual learning in humans. Unlike neural networks, humans that were trained on temporally autocorrelated task objectives (focussed training) learned to perform new tasks more effectively, and performed better on a later test involving randomly interleaved tasks. Analysis of error… 
1 Citations
A neural network walks into a lab: towards using deep nets as models for human behavior
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It is argued that methods for assessing the goodness of fit between DNN models and human behavior have to date been impoverished, and cognitive science might have to start using more complex tasks, but doing so might be beneficial for DNN-independent reasons as well.

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