# Artificial Intelligence Questions & Answers – Inductive logic programming

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This set of Artificial Intelligence Multiple Choice Questions & Answers (MCQs) focuses on “Inductive logic programming”.

1. Which combines inductive methods with the power of first-order representations?
a) Inductive programming
b) Logic programming
c) Inductive logic programming
d) Lisp programming

Explanation: Inductive logic programming(ILP) combines inductive methods with the power of first-order representations.

2. How many reasons are available for the popularity of ILP?
a) 1
b) 2
c) 3
d) 4

Explanation: The three reasons available for the popularity of ILP are general knowledge, Complete algorithm and hypotheses.

3. Which cannot be represented by a set of attributes?
a) Program
b) Three-dimensional configuration of a protein molecule
c) Agents
d) None of the mentioned

Explanation: Because the configuration inherently refers to relationships between objects.
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4. Which is an appropriate language for describing the relationships?
a) First-order logic
b) Propositional logic
c) ILP
d) None of the mentioned

Explanation: None.

5. Which produces hypotheses that are easy to read for humans?
a) ILP
b) Artificial intelligence
c) Propositional logic
d) First-order logic

Explanation: Because ILP can participate in the scientific cycle of experimentation, So that it can produce flexible structure.
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6. What need to be satisfied in inductive logic programming?
a) Constraint
b) Entailment constraint
c) Both Constraint & Entailment constraint
d) None of the mentioned

Explanation: The objective of an ILP is to come up with a set of sentences for the hypothesis such that the entailment constraint is satisfied.

7. How many literals are available in top-down inductive learning methods?
a) 1
b) 2
c) 3
d) 4

Explanation: The three literals are available in top-down inductive learning methods are predicates, equality and inequality and arithmetic literals.

8. Which inverts a complete resolution strategy?
a) Inverse resolution
b) Resolution
c) Trilogy
d) None of the mentioned

Explanation: Because it is a complete algorithm for learning first-order theories.

9. Which method can’t be used for expressing relational knowledge?
a) Literal system
b) Variable-based system
c) Attribute-based system
d) None of the mentioned

Explanation: ILP methods can learn relational knowledge that is not expressible in attribute-based system.

10. Which approach is used for refining a very general rule through ILP?
a) Top-down approach
b) Bottom-up approach
c) Both Top-down & Bottom-up approach
d) None of the mentioned