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Quiz on Inference in First Order Logic

Total questions: 20

Worksheet time: 10mins

Name
Class
Date
1.

What is the main purpose of inference in First Order Logic (FOL)?

a)

To create random statements

b)

To memorize facts

c)

To derive new facts from known ones

d)

To eliminate all known facts

2.

Which quantifiers are used in First Order Logic?

a)

¬ and ⊕

b)

∀ and ∃

c)

∧ and ∨

d)

→ and ↔

3.

What does Universal Instantiation (UI) allow you to do?

a)

Create a new constant

b)

Negate a statement

c)

Generalize a specific instance to all cases

d)

Apply a general statement to a specific instance

4.

What is an example of Existential Generalization (EG)?

a)

If Priyanka got good marks, then someone got good marks

b)

If all students wear uniforms, then John wears a uniform

c)

If all bulbs are 60W, then one bulb is 60W

d)

If John likes ice cream, then everyone likes ice cream

5.

What is a key problem with propositionalization in FOL?

a)

It can generate too many irrelevant sentences

b)

It requires more constants

c)

It eliminates all facts

d)

It simplifies the logic too much

6.

What is the core function of an inference engine?

a)

To create random facts

b)

To apply logic to derive new facts

c)

To eliminate contradictions

d)

To memorize all known facts

7.

Which of the following describes a Horn Clause?

a)

A conjunction of all literals

b)

A statement with only negative literals

c)

A statement with no literals

d)

Disjunction of literals with ≤1 positive literal

8.

What is the first step in the resolution process?

a)

Convert statements to First-Order Logic

b)

Convert to propositional logic

c)

Negate the goal statement

d)

Apply the resolution rule

9.

What does Backward Chaining do in an inference engine?

a)

Starts with known facts and works forward

b)

Generates random facts

c)

Starts with the goal and works backward

d)

Eliminates all irrelevant facts

10.

What is the result of applying resolution to prove a statement?

a)

It eliminates all known facts

b)

It generates new facts

c)

A contradiction proves the statement is false

d)

A contradiction proves the statement is true

11.

What is the purpose of Universal Generalization (UG)?

a)

To apply a general statement to a specific instance

b)

To generalize from specific instances to all cases

c)

To negate a statement

d)

To create a new constant

12.

In First Order Logic, what does the symbol ∃ represent?

a)

Disjunction

b)

Conjunction

c)

Universal quantifier

d)

Existential quantifier

13.

What is a characteristic of First Order Logic compared to Propositional Logic?

a)

It is simpler and requires no conversion

b)

It does not allow for inference

c)

It only works with ground facts

d)

It is more expressive and uses quantifiers

14.

Which of the following best describes Forward Chaining?

a)

Goal-driven reasoning

b)

Starts from goal and works backwards

c)

Data-driven reasoning

d)

Uses depth-first search

15.

In Backward Chaining, which of the following is true?

a)

It applies rules from known facts to reach a conclusion

b)

It begins with a goal and works backward to verify known facts

c)

It always uses breadth-first search

d)

It is not used in expert systems

16.

What type of clause is this: ¬p ∨ ¬q ∨ r?

a)

Definite Clause

b)

Conjunctive Clause

c)

Horn Clause

d)

Atomic Clause

17.

Which of the following is an example of a definite clause?

a)

¬P ∨ Q ∨ R

b)

King(x) ∧ Greedy(x) ⇒ Evil(x)

c)

P ∨ Q

d)

¬King(x) ∨ Evil(x)

18.

What is the final goal of applying the resolution method?

a)

To match a goal to sub-goals

b)

To convert into first-order clauses

c)

To identify all known facts in the system

d)

To reach a contradiction and prove the theorem

19.

In the resolution method, what is the form of knowledge base required?

a)

Disjunctive Normal Form (DNF)

b)

First-order normal form

c)

Horn clause form

d)

Conjunctive Normal Form (CNF)

20.

In the resolution method, what is the result of resolving the following two clauses?

Clause 1: ¬Animal(x) ∨ Eats(John, x)
Clause 2: Animal(Apple)

a)

Eats(John, Apple)

b)

¬Eats(John, Apple)

c)

Animal(Apple) ∨ Eats(John, x)

d)

No resolution possible