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A Cognitive Science Based Machine Learning Architecture

Sidney K. D’Mello, Stan Franklin, Uma Ramamurthy, Bernard J. Baars

发表年份
2006
引用次数
17
访问权限
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摘要

In an attempt to illustrate the application of cognitive science principles to hard AI problems in machine learning we propose the LIDA technology, a cognitive science based architecture capable of more human-like learning. A LIDA based software agent or cognitive robot will be capable of three fundamental, continuously active, humanlike learning mechanisms:
\n1) perceptual learning, the learning of new objects, categories, relations, etc.,
\n2) episodic learning of events, the what, where, and when,
\n3) procedural learning, the learning of new actions and action sequences with which to accomplish new tasks. The paper argues for the use of modular components, each specializing in implementing individual facets of human and animal cognition, as a viable approach towards achieving general intelligence.

关键词

Computer scienceArtificial intelligenceLIDACognitive architectureMulti-task learningRobot learningInstance-based learningActive learning (machine learning)Machine learningCognition

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