---
title: "Expert system architecture"
subject: "Artificial Intelligence"
chapter: 7
key: "semester_6/artificial_intelligence:expert-system-architecture"
source: https://www.bctengineer.com/q/semester_6/artificial_intelligence/expert-system-architecture
site: BCT Engineering
---

# Expert system architecture

Artificial Intelligence · Chapter 7: Application of AI

- Asked in: 2069 Poush, 8 marks; 2070 Magh, 6 marks; 2071 Magh, 2+4 marks; 2072 Magh, 6 marks; 2073 Magh, 5 marks; 2075 Baisakh, 2+6 marks (asked 6 times)
- Video: [Expert System Architecture In Artificial Intelligence Explained (HINDI)](https://www.youtube.com/watch?v=LhqjTyGj7lk) — 5 Minutes Engineering
- Answer checked by Claude Opus 5.5 (high effort) on 2026-10-14
- Page: https://www.bctengineer.com/q/semester_6/artificial_intelligence/expert-system-architecture
- Whole chapter: https://www.bctengineer.com/md/semester_6/artificial_intelligence/chapter-7

## Question

What is an expert system? Explain the general architecture of an expert system (draw the block diagram and explain all blocks).

## Short answer

An expert system is a program with expert-level knowledge in a narrow domain. Its architecture includes knowledge base, inference engine, working memory, user interface, explanation facility, and knowledge acquisition facility.

## Answer

An **expert system (ES)** is a computer program that holds the knowledge of human experts in a narrow domain and uses it to give advice or solve problems at expert level (e.g. MYCIN for diagnosing infections, DENDRAL, PROSPECTOR).

#### Architecture
```text
   User
    |  ^
    v  |
 +--------------------+      +-----------------------+
 |   User interface   |<---->|  Explanation          |
 +---------+----------+      |  facility             |
           |                 +-----------+-----------+
           v                             |
 +--------------------+      +-----------v-----------+
 |  Inference engine  |<---->|   Knowledge base      |
 | (reasoning control)|      |  (facts + rules)      |
 +---------+----------+      +-----------^-----------+
           |                             |
           v                 +-----------+-----------+
 +--------------------+      | Knowledge acquisition |<-- Expert /
 |  Working memory    |      | facility              |    knowledge
 | (case facts)       |      +-----------------------+    engineer
 +--------------------+
```

#### Blocks
1. **Knowledge base:** stores domain knowledge as facts and, mostly, IF-THEN production rules (also frames or semantic nets). It is kept separate from the reasoning mechanism.
2. **Inference engine:** the reasoning part. It matches rules against known facts and derives new conclusions using **forward chaining** (data-driven) or **backward chaining** (goal-driven). It also resolves conflicts when several rules apply.
3. **Working memory (global database):** holds the facts of the current case, user inputs and intermediate conclusions.
4. **User interface:** lets the user enter data and see results, usually through questions and answers or menus in language close to natural language.
5. **Explanation facility:** explains how a conclusion was reached ("How?") and why a question is asked ("Why?"), which builds trust and helps debugging.
6. **Knowledge acquisition facility:** helps the knowledge engineer and domain expert enter, edit and check knowledge in the knowledge base.

#### Roles of people
- **Domain expert:** source of knowledge.
- **Knowledge engineer:** encodes the expert's knowledge.
- **End user:** consults the system.

Example rule: IF fever AND rash AND cough THEN disease = measles (CF 0.8).

## Check yourself

The answer's key points as multiple-choice questions, with the correct option and why.

1. What does the inference engine of an expert system do?
   A. Stores the facts and rules of the domain
   B. Matches rules against known facts to derive new conclusions by forward or backward chaining
   C. Displays results to the user
   D. Lets the expert type in new rules
   Answer: B. The inference engine is the reasoning part; it applies rules to facts, using forward (data-driven) or backward (goal-driven) chaining, and resolves conflicts. (Key point: Inference engine role)

2. What is held in the working memory (global database)?
   A. Permanent domain rules from the expert
   B. The explanation of How and Why
   C. Facts of the current case, user inputs and intermediate conclusions
   D. The program code of the user interface
   Answer: C. Working memory holds case-specific facts and intermediate results, whereas the knowledge base holds permanent domain knowledge. (Key point: Working memory)

3. What questions does the explanation facility answer?
   A. Who built the system and when
   B. What is the next rule and where is it stored
   C. How was a conclusion reached, and why is a question being asked
   D. Which hardware is used and how fast it runs
   Answer: C. It explains 'How?' a conclusion was reached and 'Why?' a question is asked, which builds trust and helps debugging. (Key point: Explanation facility)

4. What is the purpose of the knowledge acquisition facility?
   A. To help the knowledge engineer and expert enter, edit and check knowledge in the knowledge base
   B. To let the end user ask questions
   C. To choose between forward and backward chaining
   D. To store intermediate results of the current case
   Answer: A. This block is the tool through which expert knowledge is entered and maintained in the knowledge base. (Key point: Knowledge acquisition facility)

## Related in Artificial Intelligence

- [Knowledge acquisition in expert system](https://www.bctengineer.com/question.md?key=semester_6%2Fartificial_intelligence%3Aknowledge-acquisition-es-architecture) — Artificial Intelligence, chapter 7, asked 2×
- [Expert system development steps](https://www.bctengineer.com/question.md?key=semester_6%2Fartificial_intelligence%3Aexpert-system-development-steps) — Artificial Intelligence, chapter 7, asked 3×
- [Expert system pros and cons](https://www.bctengineer.com/question.md?key=semester_6%2Fartificial_intelligence%3Aexpert-system-advantages-disadvantages) — Artificial Intelligence, chapter 7

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