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- Shastri Lokendra
- International Computer Science Institute
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抄録
We are capable of drawing a variety of inferences effortlessly, spontaneously, and with remarkable efficiency—as though these inferences are a reflex response of our cognitive apparatus. This remarkable human ability poses a challenge for cognitive science and computational neuroscience: How can a network of slow neuron-like elements represent a large body of systematic knowledge and perform a wide range of inferences with such speed? We briefly review work in connectionist modeling that attempts to address this challenge by demonstrating how a neurally plausible network can encode a large body of semantic and episodic facts, systematic rules, and knowledge about entities and types, and yet perform a wide range of explanatory and predictive inferences within a few hundred milliseconds.
収録刊行物
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- 認知科学
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認知科学 10 (1), 45-57, 2003
日本認知科学会
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キーワード
詳細情報
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- CRID
- 1390282679459267328
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- NII論文ID
- 130004490668
- 80015820720
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- NII書誌ID
- AN1047304X
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- ISSN
- 18815995
- 13417924
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- NDL書誌ID
- 6506900
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- NDL
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可