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AS Level · Information Technology 9626

What is an expert system?

Revise What is an expert system? for Information Technology 9626 (AS Level) — revision notes, 44 practice questions and instant AI marking.

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7.1 · Chapter 7 · AS Level IT · Hodder Education

What is an Expert System?

Definition, components, how they work, how they differ from normal programs, and the role of the knowledge engineer — all in one place.

🧠 Definition

⚙️ 7 Components

🔄 IF–THEN Rules

👷 Knowledge Engineer

The Big Idea: An expert system is software that mimics the reasoning of a human specialist. Instead of being programmed to solve one fixed problem, it stores expert knowledge in a knowledge base and uses an inference engine to reason through new problems — producing possible solutions, each often with a probability, and explaining how it got there.

7.1 What is an Expert System?

Definition

An expert system is a computer-based system used to solve problems — such as providing a diagnosis — by making use of the knowledge of a number of human experts within a specific field. Unlike other problem-solving software, expert systems use reasoning to produce possible solutions. Data (often called a database of facts) is stored in the computer as the knowledge part of a knowledge base, and the system uses a set of rules that represents the reasoning.

The Medical Diagnosis Analogy

The textbook's clearest example is a medical expert system used to help doctors diagnose illness. Here's exactly how it works in practice:

Medical diagnosis — step by step

1. A doctor types the patient's symptoms into the expert system via the user interface.
2. The expert system searches its knowledge base — which contains thousands of illnesses and their associated symptoms, gathered from multiple expert doctors.
3. The inference engine compares the inputted symptoms against the knowledge base and produces a list of possible diagnoses, each usually with a percentage probability.
4. The doctor then applies their own clinical experience to choose the most likely diagnosis from the list produced.

This is the pattern for all expert systems: human provides input → inference engine reasons through the knowledge base → system outputs possibilities + probabilities → human expert makes the final call. The system assists; it does not replace the expert.

When Expert Systems CAN and CANNOT Be Used

✅ CAN be used when…	❌ CANNOT be used when…
Human experts already operate in the field — the knowledge exists to be captured	Facts about the problem are missing or incomplete
Clearly defined rules exist for the subject area	Rules can be interpreted in multiple different ways (ambiguity makes reasoning unreliable)
Subject facts are already well established and can be stored	The problem domain has no clear rules or expert consensus

Expert Systems vs Regular Problem-Solving Programs

This comparison is a favourite exam topic. Make sure you understand the fundamental difference:

	Regular Problem-Solving Program	Expert System
What it solves	One specific, pre-defined problem only	A wide range of problems in a domain, depending on the knowledge base
How facts are stored	Facts are an integral part of the code — embedded in the programming itself	Facts are stored separately in the knowledge base — independent of the program logic
What happens when facts change	The whole program may need to be rewritten	update the knowledge base
Adaptability

Q1

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📋 Summary & Review
✅ Concepts Checklist
🧠 What to Memorise
🎯 Exam Tips

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