| 摘要 |
AN ARRANGEMENT FOR AUTOMATED TROUBLESHOOTING USING SELECTIVE ADVICE AND A LEARNING KNOWLEDGE BASE Troubleshooting expert systems are generally embodied in software for the purpose of solving difficult problems in some narrow domain of expertise. The prior art describes certain mechanics for developing or generating rules. That process is commonly known as the knowledge acquisition process. Having acquired the knowledge, our new troubleshooting arrangement eliminates the prior art separation between the expert system knowledge acquisition process and the expert system utilization process. Our new arrangement also detects and classifies invalid actions or other errors of the user in a manner that allows for the non-human expert system to advise the human user. Our arrangement interactively communicates between a user and a troubleshooting system, generates a learning knowledge base, identifies an object being tested by the user, utilizes the learning knowledge base for troubleshooting the test object, and classifies the test object as faulty or not faulty. Our arrangement structures prior actions of the user as pairs of elements in a multi-branch tree in the learning knowledge base and the compares present actions of the user with the prior actions of the user. A current signal path is generated between a first input and a first output in the system under test. Then, it can be determined whether the test object belongs to the current signal path. Responsive to the comparison of the actions of the user andresponsive to whether the test object belongs to the current path, the skill level of the user can be classified into one of a plurality of skill levels. Responsive to the skill level classification of the user, the kind of troubleshooting advice to be given the user can be classified as to one of a plurality of kinds of troubleshooting advice and thereafter the advice can be communicated to the user. Further, the output of the test object can be measured and a new current signal path can be generated and re-generated for identifying a faulty object in the system under test.
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