Artificial Intelligence Knowledge Representation and Reasoning

Question 1

What is the primary purpose of knowledge representation in AI?

Accepted Answer

To encode information about the world so an AI system can reason about it

Answer

To store data in relational databases

Answer

To compress neural network weights for faster inference

Answer

To translate natural language into machine code

Question 2

Which of the following is an example of a semantic network?

Accepted Answer

A graph where nodes represent concepts and edges represent relationships between them

Answer

A decision tree classifying email as spam or not spam

Answer

A table of pixel values from an image

Answer

A recurrent neural network processing text sequences

Question 3

In knowledge representation, what does an ontology define?

Accepted Answer

A formal specification of a set of concepts, categories, and relationships within a domain

Answer

The training procedure for deep learning models

Answer

The probability distributions over hidden variables in a model

Answer

The set of hyperparameters used during model optimization

Question 4

Propositional logic differs from first-order predicate logic in that propositional logic:

Accepted Answer

Only deals with true/false statements and lacks variables or quantifiers

Answer

Can express relationships between objects and quantify over them

Answer

Supports probabilistic reasoning under uncertainty

Answer

Handles temporal sequences of events

Question 5

What is a 'frame' in the context of knowledge representation?

Accepted Answer

A data structure that groups an object's attributes and default values into a single unit

Answer

A single image extracted from a video stream

Answer

A boundary condition applied to a neural activation function

Answer

A SQL schema for an AI training dataset

Question 6

Which inference rule states that if 'P' is true and 'P implies Q' is true, then 'Q' must be true?

Accepted Answer

Modus ponens

Answer

Modus tollens

Answer

Resolution

Answer

Abduction

Question 7

The role of an inference engine in an expert system is to:

Accepted Answer

Apply logical rules to the knowledge base to derive new facts or conclusions

Answer

Generate training data for machine learning models

Answer

Optimize neural network weights using gradient descent

Answer

Compress knowledge into a vector embedding