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CogSci 207 Midterm Review Fall 2004 Praveen Paritosh 10/18/04
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Where are we? Minsky/Turing/Miller –Computation and Cognition Markman/Lenat/Cyc –Representation Forbus/Bredeweg/Vm odel –Qualitative Reasoning Riesbeck/Lee/Batali –Natural Language Emotions Analogy and Similarity Learning/Education Consciousness Now Coming
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Cognitive modeling Psychology – mind Artificial Intelligence – computer Neuroscience – brain Philosophy – everything Linguistics – language Cognitive Science – builds up on all of the above. Goal: to understand cognition by building computational models that operate on representations.
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CogSci 207: A slice of Cognitive Modeling What are computational models and what are they capable of? –Dispel some myths: Turing/Minsky –Show some examples of models of cognitive phenomena: Qualitative Reasoning/NLP –More to come: Analogy/Emotions/Learning What are representations and what can we do with them? –Foundations: Markman/Lenat/Minsky –Some examples: Cyc/QP/Episodic –More to come: Analogy/Emotions/Education
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Computational Models Computers can do more than just what we tell them. Programs can encode library of methods/ strategies/ plans/ heuristics* and the composition of these can be completely novel and unanticipated. Programs can reflect about their own progress and decide on courses of action. * The Art Of War/ The Prince/ Andy Gordon’s work on strategies, for example.
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Representations Cyc –Predicate calculus based –Organizing principles key Mereology Ontology Domain specific knowledge Microtheories QP –Strong organizing principles –Built upon structure of everyday physical world
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Questions?
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