Cognitive Science Based Machine Learning ArchitectureD'Mello, S.K. and Franklin, Stan and Ramamurthy, Uma and Baars, Bernard J. (2006) Cognitive Science Based Machine Learning Architecture. AAAI 2006 Spring Symposium Series. American Association for Artificial Intelligence. Stanford University, Palo Alto, California, USA. Full text available as:
Official URL: http://ccrg.cs.memphis.edu/assets/papers/SS0602DMelloS.pdf AbstractIn 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: 1) perceptual learning, the learning of new objects, categories, relations, etc., 2) episodic learning of events, the what, where, and when, 3) 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.
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