Q.1 What is the primary purpose of an expert system in AI?
To perform complex calculations faster than humans
To simulate the decision-making ability of a human expert
To store large amounts of data without analysis
To replace all human jobs in an organization
Explanation - Expert systems are designed to mimic the reasoning and decision-making capabilities of human experts in a specific domain.
Correct answer is: To simulate the decision-making ability of a human expert
Q.2 Which of the following is a key component of an expert system?
Inference engine
Central processing unit
Memory cache
Compiler
Explanation - The inference engine is the reasoning mechanism of an expert system that applies logical rules to the knowledge base to deduce new information.
Correct answer is: Inference engine
Q.3 What type of knowledge does the knowledge base of an expert system contain?
Procedural and declarative knowledge
Only procedural knowledge
Only declarative knowledge
Binary code
Explanation - The knowledge base stores facts (declarative) and rules or procedures (procedural) needed for decision-making.
Correct answer is: Procedural and declarative knowledge
Q.4 Which reasoning method is commonly used in expert systems?
Forward chaining
Backward chaining
Both forward and backward chaining
Linear regression
Explanation - Expert systems can use forward chaining (data-driven) or backward chaining (goal-driven) to reach conclusions based on rules.
Correct answer is: Both forward and backward chaining
Q.5 Which of the following is an example of an expert system?
MYCIN for medical diagnosis
Google Search Engine
Microsoft Excel
Python interpreter
Explanation - MYCIN was an early expert system designed to diagnose bacterial infections and recommend antibiotics.
Correct answer is: MYCIN for medical diagnosis
Q.6 In expert systems, what is the role of the user interface?
To manage memory usage
To allow users to interact with the system
To optimize the inference engine
To store rules and facts
Explanation - The user interface provides a way for users to input queries and receive advice or explanations from the expert system.
Correct answer is: To allow users to interact with the system
Q.7 What distinguishes an expert system from a simple database?
Ability to store large amounts of data
Ability to reason and make decisions
Ability to run on computers
Ability to display data visually
Explanation - Unlike a database, an expert system can apply rules to its knowledge base and reason about information to provide expert-level advice.
Correct answer is: Ability to reason and make decisions
Q.8 Which of these is a limitation of expert systems?
Cannot handle uncertainty well
Cannot store large data
Cannot run on modern computers
Cannot be programmed in Python
Explanation - Traditional expert systems struggle with uncertainty and vague information, which later led to the development of fuzzy expert systems.
Correct answer is: Cannot handle uncertainty well
Q.9 What does the term 'rule-based system' refer to in expert systems?
A system based on programming loops
A system that uses if-then rules to make decisions
A system that uses machine learning to predict outcomes
A system that stores rules in a database
Explanation - Rule-based systems represent knowledge as a set of if-then rules which the inference engine uses to reach conclusions.
Correct answer is: A system that uses if-then rules to make decisions
Q.10 Which AI approach is most closely associated with expert systems?
Symbolic AI
Neural networks
Genetic algorithms
Deep learning
Explanation - Expert systems are a form of symbolic AI, relying on explicit symbolic representations of knowledge rather than learning from data.
Correct answer is: Symbolic AI
Q.11 What is the function of an explanation facility in an expert system?
To explain the reasoning behind decisions
To perform calculations faster
To compress the knowledge base
To connect to the internet
Explanation - An explanation facility allows users to understand how the system arrived at a particular conclusion, increasing trust and transparency.
Correct answer is: To explain the reasoning behind decisions
Q.12 Which domain is most suitable for expert system applications?
Well-structured, knowledge-rich domains
Domains with no rules
Random data analysis
Entertainment apps
Explanation - Expert systems excel in areas where expert knowledge can be encoded as rules, such as medical diagnosis or engineering troubleshooting.
Correct answer is: Well-structured, knowledge-rich domains
Q.13 Which of the following represents a fact in a knowledge base?
Patient has a fever
If patient has a fever then check for infection
Run the inference engine
Display results to user
Explanation - Facts are pieces of information about the domain, whereas rules describe how to act on those facts.
Correct answer is: Patient has a fever
Q.14 In backward chaining, reasoning starts from:
The goal and works backward to find supporting facts
The data and moves forward to derive conclusions
Random facts in the knowledge base
External database queries
Explanation - Backward chaining is goal-driven reasoning, starting with a hypothesis and checking if the known facts support it.
Correct answer is: The goal and works backward to find supporting facts
Q.15 Which component of an expert system selects which rule to apply next?
Inference engine
Rule interpreter
Knowledge base
Database manager
Explanation - The inference engine is responsible for controlling the reasoning process, deciding which rules to fire based on the facts.
Correct answer is: Inference engine
Q.16 What is a shell in the context of expert systems?
A software framework to build expert systems
A pre-trained AI model
A type of database
A programming language
Explanation - An expert system shell provides the core components (inference engine, user interface) so developers can input their own knowledge base.
Correct answer is: A software framework to build expert systems
Q.17 Which of these best describes forward chaining?
Reasoning starts from known facts and applies rules to infer conclusions
Reasoning starts from goals and works backward
Rules are ignored during reasoning
The system learns rules automatically
Explanation - Forward chaining is data-driven reasoning where the system applies rules to known facts to generate new facts or conclusions.
Correct answer is: Reasoning starts from known facts and applies rules to infer conclusions
Q.18 Fuzzy expert systems are designed to handle:
Uncertainty and imprecision in knowledge
Large amounts of numerical data
Only binary facts
Image processing tasks
Explanation - Fuzzy expert systems extend traditional systems to deal with degrees of truth and uncertain information using fuzzy logic.
Correct answer is: Uncertainty and imprecision in knowledge
Q.19 Which of the following is NOT a typical application of expert systems?
Medical diagnosis
Engineering troubleshooting
Weather prediction using neural networks
Financial advisory
Explanation - While weather prediction can involve AI, it is typically handled by numerical models and machine learning, not traditional rule-based expert systems.
Correct answer is: Weather prediction using neural networks
Q.20 What type of knowledge is represented by rules in an expert system?
Procedural knowledge
Declarative knowledge
Random knowledge
Geographical knowledge
Explanation - Rules in an expert system encode procedural knowledge: if certain conditions are met, then perform certain actions.
Correct answer is: Procedural knowledge
Q.21 What is the main advantage of using expert systems?
They can provide expert-level decisions quickly and consistently
They replace all human experts permanently
They require no maintenance
They are fully autonomous learning systems
Explanation - Expert systems allow organizations to utilize expert knowledge efficiently, though they still require updates and human oversight.
Correct answer is: They can provide expert-level decisions quickly and consistently
Q.22 Which method can improve an expert system’s ability to handle uncertainty?
Incorporating fuzzy logic
Increasing CPU speed
Storing more rules
Using a graphical interface
Explanation - Fuzzy logic allows the system to work with partial truths and uncertainty, which traditional binary logic cannot handle.
Correct answer is: Incorporating fuzzy logic
Q.23 Which type of expert system explains its reasoning in natural language to the user?
Explanation-based expert system
Rule-less system
Neural network system
Genetic algorithm system
Explanation - Explanation facilities in expert systems allow the system to communicate its reasoning process to users, improving transparency and trust.
Correct answer is: Explanation-based expert system
Q.24 What is the major challenge in building an expert system?
Knowledge acquisition from human experts
Choosing the programming language
Installing on a computer
Designing user interfaces
Explanation - Acquiring and formalizing expert knowledge into rules or structures for the system is often the most time-consuming and challenging part.
Correct answer is: Knowledge acquisition from human experts