← IGCSE Computer Science Paper 1

Explaining the basic operation of an AI system

Naming the parts of an AI system, what each does, and how they work together to take input, reason on data and rules or learn, and output a result that simulates intelligence.

Part of: IGCSE Computer Science 0478 — 6.3 Artificial Intelligence — Module 25

Understanding Explaining the basic operation of an AI system in IGCSE Computer Science Paper 1

What it does: The interface takes the input, the inference engine uses the rule base and knowledge base to reason, and a conclusion is shown to the user. Machine learning adapts: it uses the outcome of each result to change its data or processes, so later answers get more accurate. An expert system only simulates intelligence. It follows rules and data and does not truly understand. A fixed program follows the same steps every time. Machine learning changes based on past results.

Common mistakes: The inference engine searches the rule base for rules that match the facts. The interface only takes input and shows output. Line 2 should be: engine searches the rule base. The knowledge base holds the facts (the data). The IF-THEN rules are held in the rule base. Line 1 should be: knowledge base STORES facts.

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Learning
Duo
Which sentence describes the order of an expert system's operation correctly?
The user enters facts through the interface, the inference engine applies the rules to the knowledge base, and the answer is shownThe knowledge base asks the user questions, then the interface applies the rules and writes new facts
Matches
The rule base reasons by applying the inference engine to the user
↓
The roles are swapped: the inference engine is the part that reasons, using the rule base and knowledge base
Applying
Meanings
Term
AI system operation
Meaning
Naming the parts of an AI system, what each does, and how they work together to take input, reason on data and rules or learn, and output a result that simulates intelligence.
Practice
user answers ← INPUT from interface
Testing
Gaps
answer ← (facts, rules)
Check Answer
Spots
1INPUT answers via interface
2engine searches the interface

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Quick Questions

1. Which sentence describes the order of an expert system's operation correctly?
A. The user enters facts through the interface, the inference engine applies the rules to the knowledge base, and the answer is shown ✓
B. The knowledge base asks the user questions, then the interface applies the rules and writes new facts
The interface takes input from the user. The inference engine reasons using the rule base and knowledge base. The result is then output through the interface.
2. What does the inference engine do in an expert system?
A. It stores all the facts and rules the experts have collected
B. It matches the user's facts against the rules and knowledge base to reach a conclusion ✓
Storing facts is the job of the knowledge base. The inference engine does the reasoning.
3. Which statement best explains how an expert system simulates intelligence?
A. It reasons with stored expert knowledge and rules to give advice like a human expert ✓
B. It understands the problem in the same way a human expert thinks and feels
An expert system only simulates intelligence. It follows rules and data and does not truly understand.
4. Which is the best description of how a machine learning program adapts?
A. It uses the results of its past actions to change its own processes or data so it performs better next time ✓
B. A programmer must rewrite its code each time it makes a mistake
Machine learning adapts by itself. It changes its own processes or data based on what happened before.
5. Which answer uses the correct key term for the part of an expert system that holds the if-then statements?
A. Knowledge base
B. Rule base ✓
The rule base holds the rules. The knowledge base holds the facts and data about the subject.

Match the Pairs

inference engine → The part of an expert system that applies the rules to the knowledge base to reach a conclusion
knowledge base → The part of an expert system that stores the facts and data about the subject
An expert system operates in order: the user answers questions, the engine applies the rules to the data, then the result is output → interface -> inference engine + rule base -> conclusion
A machine learning program adapts by changing its own processes or data after each result so it improves over time → result -> update data -> better next answer
The rule base reasons by applying the inference engine to the user → The roles are swapped: the inference engine is the part that reasons, using the rule base and knowledge base
Machine learning follows fixed rules and never changes its own data → Machine learning adapts and learns, changing its own processes or data. It is a fixed program that does not change

Key Term

AI system operation
Naming the parts of an AI system, what each does, and how they work together to take input, reason on data and rules or learn, and output a result that simulates intelligence.

Fill in the Blanks

1. answer ← inference_engine(facts, rules)
Hint: Type the name of the expert system part that applies the rules to the facts to reach a conclusion.
2. facts ← read(knowledge_base) rules ← read(rule_base)
Hint: Type the name of the part that stores the facts and data about the subject.
3. OUTPUT conclusion TO interface
Hint: Type the part of the system that shows the result to the user and takes their input.
4. IF prediction ≠ actual THEN rules ← update(rules, data) ENDIF
Hint: Type the comparison operator that means the program's guess was wrong, so it adapts its rules.
5. FOR EACH example IN training_data learn(example) NEXT example
Hint: Type the variable name for the stored data that a machine learning program learns from.

Spot the Error

Question 1
A INPUT answers via interface
B engine searches the interface
C engine matches rules to facts
D OUTPUT conclusion to user
Line B — The inference engine searches the rule base for rules that match the facts. The interface only takes input and shows output. Line 2 should be: engine searches the rule base
Question 2
A knowledge base STORES rules
B rule base STORES IF-THEN rules
C engine APPLIES rules to facts
Line A — The knowledge base holds the facts (the data). The IF-THEN rules are held in the rule base. Line 1 should be: knowledge base STORES facts
Question 3
A data = write_rules_by_hand()
B model = learn_patterns(data)
C model.adapt(new_data)
D output = model.predict(x)
Line A — A machine learning system learns from example data. It does not rely on rules written by hand, which is how an expert system works. Line 1 should load examples, e.g. data = load_examples()
Question 4
A FOR each new example
B ignore the correct answer
C adjust own process if wrong
D NEXT
Line B — To learn, the program must compare its guess with the correct answer so it can see if it was wrong and adapt. Ignoring the answer means it cannot improve. Line 2 should be: compare guess to answer
Question 5
A RULE: IF fever AND rash
B THEN CONCLUDE measles
C FACTS: fever, cough
D MATCH: rule fires
Line C — The rule only fires if the facts match its conditions. The facts must include both fever and rash. With cough instead of rash, the rule would not fire. Line 3 should be: FACTS: fever, rash

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