Expert systems are able to explain why they arrive at a particular solution.

Question

BlackTom AI · Accepted Answer

Expert systems typically include an explanation facility that can justify conclusions by showing the rules and facts used, so True.

1. Relevant knowledge points and concepts
- Expert systems are a class of AI that encode domain knowledge as rules or facts (knowledge base) and use an inference engine to derive conclusions from that knowledge.
- Explanation facilities are a designed component of many expert systems; they provide human-readable traces of the inference process (rules fired, facts matched, chaining direction).
- Common architectures: forward chaining (data-driven) and backward chaining (goal-driven) both lend themselves to producing sequences of applied rules that can be reported to users.

2. Step-by-step reasoning process
- A user poses a query or supplies data.
- The inference engine matches data against rule antecedents and activates rules whose conditions are satisfied.
- Each time a rule fires, the system records the rule identifier, the matched facts, and the resulting assertion.
- The explanation module retrieves this record and formats it as a WHY (why was this conclusion reached?) or HOW (how did the system arrive at this result?) answer for the user.

3. Intermediate steps (explicit trace example)
- Fact A matches antecedent of Rule 1 -> Rule 1 fires -> asserts Fact B.
- Fact B plus Fact C match antecedent of Rule 2 -> Rule 2 fires -> concludes Conclusion X.
- Explanation: “Conclusion X was reached because Rule 2 fired; Rule 2 required B and C; B was produced by Rule 1 because A was present.”

4. Why the correct answer is correct
- The defining feature of classical expert systems is not only to reach conclusions but to make their reasoning auditable and intelligible. The presence of an explicit rule base and a control mechanism makes it straightforward to produce explanations of the inference chain.

5. Why the other option is incorrect
- Choosing False would imply expert systems cannot explain their solutions. That is incorrect for classical expert systems, which were specifically designed with explanation components. (Note: some modern AI models like deep neural networks are less transparent, but those are not typically labeled as classical expert systems.)

6. Conclusion
- Given the rule-based architecture and built-in explanation facilities of expert systems, the correct answer is True, which matches the provided answer.

Expert systems are able to explain why they arrive at a particular solution. 判断题

类似问题

Which of the following is a DISADVANTAGE of Expert Systems?

Which of the followings are the reason behind the usage of Expert System?i. To preserve knowledge.ii. To completely replace the human experts. iii. To train new employees.iv. To help in emergency situations.

Which of the following is not a true statement about expert systems?

Which of the following is not a limitation of expert systems?

Which of the following represents knowledge as a set of rules?

Which of the following best explains why expert systems can outperform human experts in certain tasks?

Expert systems operate primarily through:

An AI system designed to diagnose diseases using predefined rules is an example of:

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