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Arbitrating Computational Models of Observational Learning.
Neuron ( IF 14.7 ) Pub Date : 2020-05-20 , DOI: 10.1016/j.neuron.2020.04.028
Bryan Gonzalez 1 , Luke J Chang 1
Affiliation  

How do we learn in the absence of direct experience? In this issue of Neuron, Charpentier et al. (2020) proposes a new computational account of observational learning, which arbitrates between choice imitation and goal emulation.

中文翻译:

仲裁观察学习的计算模型。

在没有直接经验的情况下我们该如何学习?在本期《神经元》中,Charpentier等人。(2020)提出了一种新的观察学习计算方法,该方法在选择模仿和目标仿真之间进行仲裁。
更新日期:2020-05-20
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