1. Definition

An Expert System is a computer program that uses knowledge and reasoning rules to solve problems or make decisions in a specific domain, similar to how a human expert would.

They were among the first practical AI applications (popular in the 1970s–1990s) and are still used in areas where domain-specific expertise is required.

2. Key Components of Expert Systems

1. Knowledge Base
   • Contains facts and rules about the domain (like a doctor’s knowledge of symptoms and diseases).
2. Inference Engine
   • The reasoning mechanism that applies rules from the knowledge base to known facts to derive conclusions.
3. User Interface
   • Allows users to interact with the system by inputting problems and receiving advice or solutions.
4. Explanation Facility (optional)
   • Explains how the system arrived at a conclusion.
5. Knowledge Acquisition Module (optional)
   • Helps experts add new knowledge to the system.

3. How Expert Systems Work

1. User inputs a query/problem.
2. The inference engine checks the knowledge base for relevant facts and rules.
3. The system applies logical reasoning (forward chaining or backward chaining).
4. Output is provided to the user (solution, recommendation, or diagnosis).

4. Types of Expert Systems

• Rule-Based: Uses IF-THEN rules (most common).
• Frame-Based: Uses structured knowledge representations.
• Hybrid: Combines rules, logic, and machine learning.

5. Applications of Expert Systems

• Medical Diagnosis – MYCIN (early system for infectious diseases).
• Engineering – DENDRAL (used in chemistry to analyze compounds).
• Business & Finance – Loan approvals, investment analysis.
• Customer Support – Troubleshooting guides, chat-like systems.
• Manufacturing – Process control, fault detection.

6. Advantages

✅ Captures and reuses expert knowledge
✅ Consistency in decision-making
✅ Works 24/7 without fatigue
✅ Useful in training and education

7. Limitations

⚠️ Cannot learn or adapt on its own (unlike modern ML/AI)
⚠️ Narrow focus (works only in one domain)
⚠️ Expensive and time-consuming to build knowledge bases
⚠️ May become outdated if not regularly updated

8. Examples of Expert Systems

• MYCIN – Diagnosed bacterial infections (medical field).
• DENDRAL – Chemical analysis system.
• CLIPS – General-purpose expert system shell.
• XCON (DEC) – Configured computer systems.

✅ In short: Expert Systems are rule-driven AI systems that solve problems in a narrow domain by mimicking human expert reasoning.