What is an Expert System?

Source: Dev.to

Overview

An expert system is a computer program that contains specialized knowledge and can make decisions or solve problems in a way that mimics a human expert.

Components

Knowledge Base – the “brain library”

The knowledge base stores the expert knowledge, which consists of:

• Facts – simple statements, e.g.:

  My temperature is 103°F
  I have a headache

• Rules – “if‑then” statements that connect facts, e.g.:

  IF temperature > 100°F AND headache = yes
  THEN disease might be fever

Inference Engine – the “thinking machine”

The inference engine uses the knowledge base to draw conclusions. It operates in two common ways:

Forward Chaining

Starts from known facts and derives new information.

Facts → "I have high temperature" + "I have headache"
        ↓
    Thinking... 🤔
        ↓
Conclusion → "You might have fever!"

Backward Chaining

Starts from a goal and works backward to verify required facts.

Goal → "Do I have fever?"
        ↓
    What facts do I need? 🤔
        ↓
Check → Do I have high temperature? Yes!
        Do I have headache? Yes!
        ↓
Conclusion → "Yes, you might have fever!"

Applications

• Medical assistance – programs that help doctors diagnose illnesses.
• Agricultural assistance – tools that advise farmers on irrigation, fertilization, and crop management.

Expert System Shells

Ready‑made toolkits that provide the underlying infrastructure; developers add domain‑specific knowledge. Popular shells include:

• CLIPS
• Jess

Knowledge Representation Techniques

• If‑Then Rules – a recipe‑book style of decisions.
• Decision Trees – a choose‑your‑own‑adventure style structure.
• Frames – organized collections of related information, similar to file folders.

Characteristics of Good Expert Systems

• Validation – ensuring the knowledge and conclusions are correct.
• Explanation – the ability to justify decisions (e.g., “I think you have fever because your temperature is high and you have a headache”).
• Data Sensitivity – careful handling of private or sensitive information.

Example: PITUMBERG

PITUMBERG (or a similarly named system) demonstrates how expert systems can be applied to specific fields, illustrating the integration of a knowledge base and inference engine to provide domain‑specific assistance.

Summary

An expert system = Knowledge Base (what it knows) + Inference Engine (how it thinks).
These systems assist doctors, farmers, engineers, and many other professionals by combining extensive knowledge with logical reasoning—much like a helpful robot friend.