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What's in a Deep Model? A Characterization of Knowledge Depth in Intelligent Safety Systems

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Proceedings of the Tenth International Joint Conference on Artificial Intelligence. Knowledge Representation. Pages 559-561.

Abstract

While one can characterize deep and shallow models at a high level of abstraction and contrast their relative merits in a general way, this . provides l!ttle direction for ~o~ledge engineering. In particular, the f1eld lacks a clear defm1t1on of 'knowledge depth' and lacks gu_idelines . . regarding t~e appropriate depth Of modelS ~Or a g1ven application; . rn thiS P.aper we provide a very s1mple operational def1n!~on of knowledge depth' and use it to exam1ne the opportumties for varying depth in intelligent safety sy_stems. The paper illust~ates a domain-independent mode of analysis for examining progressively deeper models of expertise, and sketches some domain-specific guidelines for constructing intelligent safety systems. We draw ur.on examples from the domains of nuclear reactor managemen , chemical plant control, and management of computer installation operations.

David Klein, and Timothy W. Finin. 1987. What's in a Deep Model? A Characterization of Knowledge Depth in Intelligent Safety Systems. In Proceedings of the Tenth International Joint Conference on Artificial Intelligence, IJCAI-87. IJCAI, 559–561. https://ijcai.org/proceedings/1987/111
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