Conditioning, how animals learn to associate two or more events, is one of the most influential paradigms in learning theory. It is nevertheless unclear how current models of associative learning can accommodate complex phenomena without ad hoc representational assumptions. We propose to embrace deep neural networks to negotiate this problem.

中文翻译：

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联想学习应该深入

条件反射，动物如何学会将两个或多个事件联系起来，是学习理论中最有影响力的范式之一。然而，目前尚不清楚当前的联想学习模型如何在没有临时表征假设的情况下适应复杂现象。我们建议采用深度神经网络来解决这个问题。