IG1 G6T6_1 Expert Systems

What is an expert system?

• An expert system is a computer program that simulates the judgment and behavior of a human or an organization that has expert-level knowledge and experience in a specific field.

• A tool for creating websites without coding.

• A database that stores expert opinions.

• A program that only performs basic calculations.

List two main components of an expert system.

• User interface

• Data processor

• Knowledge base, Inference engine

• Rule base

How does an expert system differ from a traditional program?

• A traditional program uses machine learning to adapt over time.

• An expert system differs from a traditional program by using knowledge-based reasoning to make decisions, whereas a traditional program executes fixed algorithms.

• An expert system is designed to perform basic arithmetic operations.

• An expert system relies solely on user input to make decisions.

What role does knowledge representation play in expert systems?

• Knowledge representation is irrelevant to decision-making.

• Knowledge representation is only used for data storage.

• Expert systems do not require knowledge representation.

• Knowledge representation enables expert systems to store and manipulate domain-specific information for reasoning and decision-making.

Define inference engine in the context of expert systems.

• An inference engine is a hardware component that processes data.

• An inference engine is a user interface for expert systems.

• An inference engine is a type of database used for storing data.

• An inference engine is a component that applies rules to a knowledge base to derive conclusions in expert systems.

What is the purpose of a knowledge base in an expert system?

• The purpose of a knowledge base in an expert system is to store and manage domain-specific knowledge for problem-solving.

• To replace human experts in all decision-making processes.

• To provide a user interface for the expert system.

• To generate random data for testing purposes.

Explain the term 'rule-based system' as it relates to expert systems.

• A rule-based system is a type of database management system.

• A rule-based system is an expert system that uses 'if-then' rules to make decisions or draw conclusions.

• A rule-based system is an AI that learns from user interactions.

• A rule-based system relies solely on statistical analysis.

What are some common applications of expert systems?

• Weather prediction

• Cooking recipes

• Medical diagnosis, financial forecasting, technical troubleshooting, customer support.

• Social media management

How do expert systems handle uncertainty?

• Expert systems rely solely on deterministic algorithms.

• Expert systems ignore uncertainty completely.

• Expert systems use only rule-based reasoning without any probabilistic methods.

• Expert systems use probabilistic reasoning, fuzzy logic, and Bayesian networks to manage uncertainty.

What is the significance of user interface in expert systems?

• The user interface complicates the interaction with expert systems.

• User interfaces only serve aesthetic purposes in expert systems.

• The user interface is irrelevant to the performance of expert systems.

• The user interface is significant as it enhances usability and facilitates effective interaction between users and the expert system.