Expert Systems (CIE IGCSE ICT)

An Expert system is a computer program that uses artificial intelligence to replicate the decision-making abilities of a human expert in a specific field.

Purpose of an Expert System

• Solve complex problems
• Expert systems are designed to handle complex problems that usually require human expertise
• Enhance decision-making
• They assist in making informed decisions by providing accurate and reliable recommendations based on the available data
• Save time and resources
• Expert systems can process vast amounts of data quickly, reducing the time and effort required by human experts
• Consistency and accuracy
• They ensure consistent and accurate results by eliminating human error and bias
• Knowledge preservation
• Expert systems store and preserve the knowledge of experts, ensuring it is not lost when the expert retires or is unavailable

Uses of Expert Systems

• Mineral prospecting
  • Analyse geological data
  • Identify potential locations for mineral deposits
• Car engine fault diagnosis
  • Determine issues within engine components
  • Suggest repair options and maintenance schedules
• Medical diagnosis
  • Analyse patient symptoms and medical history
  • Suggest possible diagnoses and treatment plans
• Chess games
  • Evaluate possible moves based on the game state
  • Plan strategic moves to increase chances of winning
• Financial planning
  • Evaluate investment options and risks
  • Provide personalised financial advice
• Route scheduling for delivery vehicles
  • Calculate optimal routes based on factors like distance, traffic, and time constraints
  • Reduce fuel consumption and improve efficiency
• Plant and animal identification
  • Analyse physical characteristics and habitat data
  • Identify species and provide relevant information
• Career recommendations
  • Ask the user a series of questions / analyse existing qualifications
  • Make recommendations on career choices

Components of an Expert System

• User Interface:
• Allows users to interact with the expert system
• Provides a platform for inputting data and receiving recommendations or solutions
• Designed for ease of use and accessibility
• Inference Engine:
• A core component of the expert system that performs logical reasoning
• Applies rules from the rules base to the data from the knowledge base
• Mimics human decision-making processes to generate conclusions
• Knowledge Base:
• Repository for domain-specific information, facts, and data
• Contains expertise gathered from human experts or other reliable sources
• Essential for the inference engine to make accurate recommendations
• Rules Base:
• Stores logical rules and relationships governing the domain
• Guides the inference engine in applying reasoning to the data
• Rules can be modified or updated as new information becomes available
• Explanation System:
• Provides transparency in the decision-making process
• Offers detailed explanations of the expert system's reasoning and conclusions
• Enhances user trust and understanding of the system's recommendations

How an Expert System is Used to Produce Possible Solutions

• Expert systems use the knowledge base and rules base to analyse input data
• The inference engine applies rules and logic to the input data
• The system generates potential solutions or recommendations based on the applied rules
• The explanation system communicates the reasoning behind the suggested solutions