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.''
J. Sticklen and W. E. Bond, "Functional Reasoning and Functional Modelling," IEEE Expert, Institute of Electrical and Electronics Engineers (IEEE), Jan 1991.
The definitive version is available at https://doi.org/10.1109/64.79704
Keywords and Phrases
Artificial Intelligence; Functional Modelling; Functional Reasoning; Model-Based Reasoning
International Standard Serial Number (ISSN)
Article - Journal
© 1991 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.