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来自像人一样学习和思考的机器的证据。

Evidence from machines that learn and think like people.

机构信息

Department of Computer Science,Northwestern University,Evanston,IL

Department of Psychology,Northwestern University,Evanston,IL

出版信息

Behav Brain Sci. 2017 Jan;40:e264. doi: 10.1017/S0140525X17000139.

Abstract

We agree with Lake et al.'s trenchant analysis of deep learning systems, including that they are highly brittle and that they need vastly more examples than do people. We also agree that human cognition relies heavily on structured relational representations. However, we differ in our analysis of human cognitive processing. We argue that (1) analogical comparison processes are central to human cognition; and (2) intuitive physical knowledge is captured by qualitative representations, rather than quantitative simulations.

摘要

我们同意 Lake 等人对深度学习系统的深刻分析,包括它们高度脆弱,并且需要比人类多得多的例子。我们也同意人类认知依赖于结构化的关系表示。然而,我们在人类认知处理的分析上存在分歧。我们认为:(1)类比比较过程是人类认知的核心;(2)直观的物理知识是由定性表示而不是定量模拟来捕捉的。

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