Which of the following is a DISADVANTAGE of Expert Systems?

Question

BlackTom AI · Accepted Answer

Expert systems encapsulate specialist knowledge as rules, a knowledge base, and an inference engine, so their main strengths and weaknesses follow from how that knowledge is acquired, represented, and maintained.

1. Relevant knowledge points and concepts
- Knowledge acquisition: capturing expert knowledge requires interviews, modeling, and translation into explicit rules; this is time-consuming and needs skilled knowledge engineers.
- Rule-based representation: rules are explicit and brittle; modifying them when domain knowledge changes often requires careful, manual edits.
- Maintenance cost: updating, testing, and validating changes is labor-intensive, so lifecycle costs can be high.
- Other properties: expert systems can handle symbolic reasoning well, can be extended to handle numerical data or integrated with other tools, and do not inherently require physical hardware like robots.

2. Step-by-step reasoning evaluating each option
- Option A: Claims expert systems cannot process numerical data effectively. This is false in general: while traditional rule-based systems emphasize symbolic knowledge, they can represent and compute numerical values or be combined with numerical modules. So A is not a broadly true disadvantage.
- Option B: States expert systems always produce incorrect results when used outside their domain. That’s an overstatement: they may produce unreliable or irrelevant answers outside their knowledge domain (they are brittle), but “always produce incorrect results” is too absolute and therefore incorrect.
- Option C: States expert systems are expensive to build and difficult to update when domain knowledge changes. This matches the known facts: eliciting expert knowledge, encoding it, and maintaining the rule base is costly and labor-intensive; changes to domain knowledge require careful re-engineering and re-validation.
- Option D: Asserts expert systems require a physical robot to implement recommendations. That is incorrect—expert systems are software; implementation of actions may be manual or automated but a robot is not required.

3. Intermediate steps / supporting details
- Knowledge acquisition involves repeated expert interviews and validation cycles → increases initial cost.
- Rule edits must preserve consistency and may have unforeseen interactions → updates are risky and time-consuming.
- Ongoing maintenance and verification add to total cost of ownership.

4. Why the correct answer is correct
Option C directly identifies the recognized disadvantage: high development cost plus the difficulty of updating encoded expert knowledge as the domain evolves. This is a standard limitation cited in AI and knowledge-engineering literature.

5. Why other options are incorrect (brief)
- A: Too narrow/incorrect—numerical processing is possible.
- B: Overstated absolute claim—may be unreliable outside domain but not guaranteed always wrong.
- D: Factually incorrect—no physical robot is required.

Conclusion: The correct answer is C. This matches the provided answer: "C. Expert systems are expensive to build and difficult to update when domain knowledge changes."

Which of the following is a DISADVANTAGE of Expert Systems?Single choice

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