Expert System IGCSE Quiz

What is knowledge representation in expert systems?

• Techniques for designing user interfaces

• Strategies for managing financial data

• Ways to communicate with other systems

• Methods used to store and manipulate information within the system

Explain the role of the inference engine in expert systems.

• It only provides user interface for the expert system.

• It applies logical reasoning to the knowledge base in order to draw conclusions and make recommendations.

• It has no role in the expert system.

• It is responsible for data storage and retrieval.

How do rule-based expert systems function?

• By using a set of predefined rules and logical reasoning

• By randomly guessing the solution

• By relying on emotions and intuition

• By using trial and error

What are the advantages of using expert systems in problem-solving?

• Expert systems cannot capture or preserve the knowledge of experts

• Expert systems can provide consistent and accurate solutions, can work 24/7 without fatigue, and can capture and preserve the knowledge of experts.

• Expert systems can only work during office hours

• Expert systems provide inconsistent and inaccurate solutions

What are the limitations of expert systems in real-world applications?

• Ability to handle uncertainty and lack of common sense reasoning

• Limitations such as inability to handle uncertainty, difficulty in acquiring knowledge, and lack of common sense reasoning.

• Inability to handle uncertainty and ease in acquiring knowledge

• Ease in acquiring knowledge and lack of common sense reasoning

Describe the process of knowledge representation in expert systems.

• Using artificial intelligence to generate knowledge

• Storing knowledge in a physical library

• Converting knowledge into binary code

• Capturing and organizing knowledge in a way that can be used by the system to make decisions or solve problems.

Discuss the importance of the inference engine in expert systems.

• The inference engine has no impact on the decision-making process in expert systems.

• The inference engine is only used for data storage in expert systems.

• The inference engine is crucial for making decisions and drawing conclusions in expert systems.

• Expert systems can function effectively without the use of an inference engine.

Compare and contrast rule-based expert systems with other types of expert systems.

• Rule-based expert systems use neural networks, while other types use if-then rules.

• Rule-based expert systems are based on statistical analysis, while other types use if-then rules.

• Rule-based expert systems use fuzzy logic, while other types use if-then rules.

• Rule-based expert systems use if-then rules, while other types may use different approaches.

Explain how expert systems can improve decision-making in various industries.

• Expert systems have no impact on decision-making

• Expert systems are too expensive for industries to implement

• Expert systems can improve decision-making by providing accurate and consistent support based on knowledge and rules.

• Expert systems can only provide inaccurate and inconsistent support

What are the ethical considerations when using expert systems in decision-making processes?

• Transparency, accountability, fairness, and potential biases

• Confidentiality, privacy, security, and data protection

• Complexity, ambiguity, subjectivity, and inconsistency

• Speed, efficiency, accuracy, and cost-effectiveness