Artificial Intelligence Knowledge Representation and Reasoning 2

Question 1

What distinguishes deductive reasoning from inductive reasoning in AI?

Accepted Answer

Deductive reasoning draws specific conclusions that are guaranteed from general premises; inductive reasoning generalizes from specific observations

Answer

Inductive reasoning is always more accurate than deductive reasoning

Answer

Deductive reasoning works only with probabilistic data

Answer

Inductive reasoning requires complete knowledge of all facts

Question 2

In forward chaining, an AI system:

Accepted Answer

Starts from available facts and applies rules to derive new conclusions until the goal is reached

Answer

Starts from a goal and works backward to find supporting facts

Answer

Randomly selects rules to apply until a solution is found

Answer

Uses neural network layers to propagate activations forward

Question 3

Backward chaining is best described as:

Accepted Answer

Starting from a goal hypothesis and working backward to find facts that support it

Answer

Processing data in reverse chronological order

Answer

Training a neural network by reversing gradient flow

Answer

Reversing the order of rules in a knowledge base

Question 4

Fuzzy logic is used in AI primarily to:

Accepted Answer

Represent and reason about degrees of truth in situations involving uncertainty or vagueness

Answer

Handle binary true/false decisions more efficiently

Answer

Encrypt knowledge base entries for security

Answer

Speed up gradient computation in neural networks

Question 5

Which of the following best describes a production rule system?

Accepted Answer

A rule-based system using IF-THEN rules to represent knowledge and trigger actions

Answer

A system that generates images using generative adversarial networks

Answer

A database system that handles CRUD operations for AI data

Answer

A scheduling algorithm for parallel model training jobs

Question 6

What is the Closed World Assumption (CWA) in knowledge representation?

Accepted Answer

Any fact not known to be true is assumed to be false

Answer

All knowledge in the knowledge base is encrypted and inaccessible

Answer

The system can only reason about a fixed, finite set of objects

Answer

Unknown facts are assigned a probability of 0.5

Question 7

The Open World Assumption (OWA), used in ontologies like OWL, means that:

Accepted Answer

A fact not currently known may still be true — lack of information does not imply falsehood

Answer

All facts in the world are already stored in the knowledge base

Answer

The knowledge base is publicly accessible on the internet

Answer

The system treats all unknown facts as equally likely