A car that will not start on a cold winter day and one that will not start on a hot summer day usually indicate two very different situations. When pressed to explain the difference, we would give a winter account- "Oil is more viscous in cold conditions, and that causes . . .'' -and a summer story- "Vapor lock is a possibility in hot weather and is usually caused by . . .'' How do we build such explanations? One possibility is that understanding how the car works as a device gives us a basis for generating the explanations. But that raises another question: how do people understand devices? Model-based reasoning is a subfield of artificial intelligence focusing on device understanding issues. In any model-based-reasoning approach, the goal is to "model'' a device in the world as a computer program. Unfortunately, "model'' is a loaded term-different listeners understand the word to mean very different concepts. By extrapolation, "model-based reasoning'' can suggest several different approaches, depending on the embedded meaning of "model.''


Computer Science

Keywords and Phrases

Artificial Intelligence; Functional Modelling; Functional Reasoning; Model-Based Reasoning

International Standard Serial Number (ISSN)


Document Type

Article - Journal

Document Version

Final Version

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© 1991 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

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