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The explanation mechanism is an important feature of expert systems. It explains how the system has reached a decision and can also allow users to find out why it has asked a particular question. Because it is a rule based, the system is able to provide the user with an explanation of which rules were used during the inference process. This allows the user to make a judgement on the reliability of the decision. For example:
In the examples from the Animal-ID expert system all of the data held in the database of facts matched all of the IF THEN rules. The system could therefore confidently (1 or 100%) predict that the conclusions were true. However, if some parts of the IF THEN rules could not be matched with data held in the database of facts, the system could not be as confident.
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