Expert System MCQ: Expert systems are a type of artificial intelligence (AI) technology that copies the decision-making and problem-solving skills of a human expert in a specific field or subject. They are also referred to as knowledge-based systems or rule-based systems.
Expert System MCQ With Revision Notes
Examples of the Expert System
- DENDRAL: DENDRAL is an expert system that analyzes the mass spectra of unidentified organic compounds using a library of chemical data to identify them.
- MYCIN: An early expert system that employed backward chaining to detect issues with blood clotting, identify bacterial illnesses, and provide antibiotic prescriptions.
- PXDES: An expert system can identify lung cancer from the X Ray images and also figuring out the type and degree of the disease.
- CaDeT: A CaDeT system can diagnosis the cancer symptoms in early stage.
Expert System MCQ
- What is the main purpose of the User Interface in an expert system?
a. To store knowledge
b. To input data and interact with the user
c, To perform inference
d. To access external databases
- Which type of knowledge expert system is used to represented using “if-then” rules?
a. Procedural Knowledge
b. Declarative Knowledge
c, Structural Knowledge
d. Contextual Knowledge
- An expert system’s reasoning procedure includes ___________.
a. Collecting data
b. Deriving conclusions from available knowledge
c, Training a neural network
d. Storing data in a database
- What is the name of the procedure that involves using an expert system to get a particular conclusion or resolution?
a. Inference
b. Learning
c, Encoding
d. Observation
- Which of the following describes an expert system limitation?
a. They are not capable of learning from new data
b. They are highly susceptible to human biases
c, They can handle a wide range of tasks and domains
d. They are not cost-effective
- What is an Expert System?
a. A computer program that can think like a human
b. A program that uses machine learning to make predictions
c, A computer program that emulates the decision-making ability of a human expert
d. A program that uses artificial neural networks for image recognition
- Which of the following is not a part of an expert system?
a. Knowledge Base
b. Inference Engine
c, User Interface
d. Printer
- What do you call a rule-based system where the rules are expressly designed and not learned through data?
a. Knowledge-based system
b. Expert system
c, Neural network
d. Genetic algorithm
- Which stage of the creation of an expert system involves performance evaluation and improvement?
a. Knowledge Acquisition
b. Knowledge Representation
c, Knowledge Verification and Validation
d. Knowledge Execution
- Which of the following is an everyday application for rule-based expert systems?
a. Autonomous vehicle navigation
b. Image recognition
c, Credit card fraud detection
d. Social media analysis
- What does “backward chaining” mean in an expert system?
a. Starting with a goal and working backward to find supporting evidence
b. Starting with data and working forward to reach a conclusion
c, Collaborating with human experts to develop knowledge
d. Building a knowledge base from scratch
- In an expert system _ is the Knowledge Base contains.
a. Rules and Facts
b. Hardware components
c, Software algorithms
d. Expert opinions
- The Inference Engine in an expert system which is responsible for ____________.
a. Storing knowledge
b. Executing rules to draw conclusions
c, Providing a user-friendly interface
d. Connecting to external databases
- What is the process of gathering information from human experts and encoding it into an expert system called?
a. Inference
b. Knowledge Engineering
c, Machine Learning
d. Expertise Extraction
- What is the most popular programming language for creating expert systems?
a. Java
b. C++
c, Prolog
d. Python
- Which of the following is an example of an expert system that is effective when used for medical diagnosis?
a. Siri
b. Watson
c, Excel
d. Photoshop
- What are the main benefits of using expert systems in decision-making procedures?
a. They are always faster than human experts
b. They are not influenced by emotions or biases
c, They require minimal computational resources
d. They are easier to maintain than traditional software systems
- Which of the following is a real-time application for an expert system?
a. Weather forecasting
b. Chess-playing program
c, Email client
d. Word processing software
- Which expert system design helps the user to understand the expert system’s decisions and reasoning?
a. Black-box architecture
b. Glass-box architecture
c, Closed-box architecture
d. Open-box architecture
- Which of the following features of a rule-based expert system makes it preferable to a neural network for particular tasks?
a. Better performance on image recognition tasks
b. Easier interpretation of the decision-making process
c, Faster training time
d. Ability to handle unstructured data
- Which element of the expert system is in charge of structuring and representing knowledge in a way that the inference engine can understand?
a. Knowledge Base
b. Inference Engine
c, User Interface
d. Knowledge Acquisition System
- Which of the following is an example of an expert system used in the field of finance?
a. Spotify
b. Quicken
c, Instagram
d. Netflix
- What is a knowledge engineer’s main role in the creation of an expert system?
a. Diagnosing medical conditions
b. Designing user interfaces
c, Acquiring and encoding expert knowledge
d. Writing code for the inference engine
- Which type of expert system is more suitable for medical diagnosis?
a. Forward chaining
b. Backward chaining
c, Reinforcement learning
d. Unsupervised learning
- Which of the following criteria makes expert systems less beneficial than human experts?
a. Limited ability to handle complex problems
b. Inability to work 24/7 without rest
c, Lack of transparency in decision-making
d. High cost of development
- What is the difference between a rule-based expert system and a case-based expert system?
a. Rule-based systems use if-then rules, while case-based systems rely on past cases.
b. Rule-based systems are more efficient than case-based systems.
c, Case-based systems are rule-based systems with added complexity.
d. Case-based systems do not use rules.
- Which of the following presents a challenge when creating expert systems for fields that change quickly and dynamically?
a. Lack of available expert knowledge
b. Difficulty in encoding heuristics
c, Inability to handle uncertainty
d. Keeping the knowledge base up to date
- In a semantic network, what kind of knowledge representation is used?
a. Hierarchical
b. Sequential
c, Tabular
d. Random
- Which of the following is an example of a fuzzy expert system?
a. A weather forecasting system
b. A chess-playing program
c, A stock market prediction system
d. A medical diagnosis system
- What is the main benefit of using a production system for expert systems knowledge representation?
a. Flexibility in representing knowledge
b. Speed of execution
c, Ability to handle large amounts of data
d. Automatic knowledge acquisition
- What exactly is a “frame” in a knowledge representation that uses frames?
a. A data structure for organizing information about a specific concept or object
b. A set of rules for inference
c, A neural network layer
d. A programming language construct
- Which of the following is a representation of an expert system that interacts with consumers using natural language processing?
a. Siri
b. Excel
c, Google Maps
d. Photoshop
- Which of the following approaches is typically used by expert systems to deal with uncertainty?
a. Ignoring uncertain data
b. Assigning probabilities to facts and rules
c, Using only crisp (non-fuzzy) rules
d. Eliminating all uncertain elements from the system
- What is the main advantage of employing a hybrid expert system that blends case-based and rule-based reasoning?
a. Increased speed of execution
b. Enhanced ability to handle uncertainty
c, Reduced need for a knowledge engineer
d. Improved user interface
- Which of the following methods helps expert systems perform better by taking feedback and experience into account?
a. Rule-based reasoning
b. Case-based reasoning
c, Neural networks
d. Decision trees
- What is the main objective of a development environment or expert system shell?
a. To provide a user-friendly interface for experts
b. To automate the process of knowledge acquisition
c, To create a rule-based knowledge representation
d. To generate natural language explanations
- Which of the following could raise ethical issues when using expert systems?
a. Increased availability of expert knowledge
b. Over Reliance on automation in decision-making
c, Enhanced transparency in decision-making
d. Reduced cost of healthcare
- Which of the following is a case where an expert system is applied in the customer support industry?
a. Photoshop
b. Spotify
c. Chatbot for answering customer queries
- What does “explanation-based learning” mean in the context of expert systems?
a. Learning from experience and feedback
b. Acquiring knowledge from experts
c, Providing explanations for the system’s decisions
d. Encoding knowledge using if-then rules
- Which of the following approaches focuses on the most pertinent knowledge to increase the effectiveness of expert systems?
a. Knowledge acquisition
b. Knowledge validation
c, Knowledge pruning
d. Knowledge representation
- What is the technical word for the process of evaluating the trustworthiness and accuracy of the knowledge and reasoning of an expert system?
a. Knowledge acquisition
b. Knowledge validation
c, Knowledge representation
d. Knowledge pruning
- What is the restriction of rule-based expert systems?
a. They are not capable of handling uncertainty.
b. They require a large amount of training data.
c, They are not suitable for complex decision-making tasks.
d. They may produce explanations that are difficult for users to understand.
- Which stage of developing an expert system involves gathering knowledge from subject matter experts and encoding it in a way that computers can understand?
a. Knowledge Verification
b. Knowledge Validation
c, Knowledge Acquisition
d. Knowledge Execution
- What is the main advantage of using a forward-chaining approach in an expert system?
a. It allows for backward reasoning.
b. It starts with a goal and works towards finding a solution.
c, It is faster than backward chaining.
d. It is easier to implement.
- What is the main objective of a rule-based expert system?
a. To simulate human reasoning and decision-making
b. To process natural language text
c, To perform complex mathematical calculations
d. To create 3D graphics
- Which of the following elements of an expert system is responsible for explaining the suggestions or judgments made by the system?
a. Knowledge Base
b. Inference Engine
c, User Interface
d. Explanation Generator
- Which of the following represents a heuristic that expert systems might use?
a. A mathematical formula
b. An if-then rule
c, A decision tree
d. A neural network
- Combining various pieces of evidence to arrive at a decision in an expert system is known as ____________.
a. Inference
b. Abduction
c, Deduction
d. Induction
- Which of the following is a domain-specific expert system example?
a. Siri
b. Google Search
c, Chess-playing program
d. Microsoft Word
- Which expert system component is responsible for selecting the appropriate rules to apply during the reasoning process?
a. Knowledge Base
b. Inference Engine
c, User Interface
d. Knowledge Acquisition System