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Verification and validation with ripple-down rules
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DOI：10.1006/ijhc.1996.0013.png)
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摘要
En 中文
Verification to ensure a system's consistency and validation to meet the user's criteria are essential elements in developing knowledge-based systems for real world use. The normal practice is that there will be initial knowledge acquisition attempting to build a complete system which will (should) then be verified and validated, There may be a cycle through these steps till the system is complete, Maintenance is seen as a minor problem requiring the occasional repetition of the three stage process. The implicit assumption is that an expert has complete knowledge and that by a suitable knowledge acquisition process this is acquired. In fact, it seems rather than experts are incapable of recounting how they reach a conclusion. Rather, when asked a question they justify that their conclusion is correct and their justification is tailored to the specific context of the inquiry, Experts are best at justifying why one conclusion is to be preferred over another. This leads to a knowledge acquisition methodology, Ripple-down Rules, in which the knowledge base undergoes on-going development based on correcting errors. Each new correction or justification is considered only in the context of the same mistake being made, The method also constrains the expert's choices to ensure that any new knowledge added is valid while the knowledge base structure ensures the knowledge is verified. Verification and validation are not separate tasks, but constraints on knowledge acquisition which itself continues throughout the life of the system. This provides a closer match with the normal evolution of human knowledge and expertise. The overall approach has itself been validated by the development of a large medical expert system and through simulation studies, The medical system has been developed while in routine use and has only involved experts without any knowledge engineering support or skill in its development. (C) 1996 Academic Press Limited
Keyword:
EXPERT-SYSTEM
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