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- 第三部分 学习的四大核心支柱 >
- 注释
第2章 为什么人脑的学习能力比目前的人工智能机器更强
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Artificial neural networks primarily implement the unconscious operations of the brain: Dehaene, Lau, and Kouider, 2017.
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Artificial neural networks tend to learn superficial regularities: Jo and Bengio, 2017.
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Generation of images that confuse humans as well as artificial neural networks: Elsayed et al., 2018.
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Artificial neural network that learns to recognize CAPTCHAs: George et al., 2017.
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Critique of the learning speed in artificial neural networks: Lake, Ullman, Tenenbaum, and Gershman, 2017.
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Lack of systematicity in artificial neural networks: Fodor and Pylyshyn, 1988; Fodor and McLaughlin, 1990.
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Language of thought hypothesis: Amalric, Wang, et al., 2017; Fodor, 1975.
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Learning to count as program inference: Piantadosi, Tenenbaum, and Goodman, 2012; see also Piantadosi, Tenenbaum, and Goodman, 2016.
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Recursive representations as a singularity of the human species: Dehaene, Meyniel, Wacongne, Wang, and Pallier, 2015; Everaert, Huybregts, Chomsky, Berwick, and Bolhuis, 2015; Hauser, Chomsky, and Fitch, 2002; Hauser and Watumull, 2017.
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Human singularity in coding an elementary sequence of sounds: Wang, Uhrig, Jarraya, and Dehaene, 2015.
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Acquisition of geometrical rules—slow in monkeys, ultrafast in children: Jiang et al., 2018.
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The conscious human brain resembles a serial Turing machine: Sackur and Dehaene, 2009; Zylberberg, Dehaene, Roelfsema, and Sigman, 2011.
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Fast learning of word meaning: Tenenbaum, Kemp, Griffiths, and Goodman, 2011; Xu and Tenenbaum, 2007.
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Word learning based on shared attention: Baldwin et al., 1996.
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Knowledge of determiners and other function words at twelve months: Cyr and Shi, 2013; Shi and Lepage, 2008.
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Mutual exclusivity principle in word learning: Carey and Bartlett, 1978; Clark, 1988; Markman and Wachtel, 1988; Markman, Wasow, and Hansen, 2003.
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Reduced reliance on mutual exclusivity in bilinguals: Byers-Heinlein and Werker, 2009.
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Rico, a dog who learned hundreds of words: Kaminski, Call, and Fischer, 2004.
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Modelling of an “artificial scientist”: Kemp and Tenenbaum, 2008.
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Discovering the causality principle: Goodman, Ullman, and Tenenbaum, 2011; Tenenbaum et al., 2011.
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The brain as a generative model: Lake, Salakhutdinov, and Tenenbaum, 2015; Lake et al., 2017.
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Probability theory is the logic of science: Jaynes, 2003.
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Bayesian model of information processing in the cortex: Friston, 2005. For empirical data on hierarchical passing of probabilistic error messages in the cortex, see, for instance, Chao, Takaura, Wang, Fujii, and Dehaene, 2018; Wacongne et al., 2011.
第二部分 人脑如何学习
