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ai_practical Quiz

Total questions: 20

Worksheet time: 10mins

Name
Class
Date
1.

Which logic deals with propositions and their relationships using logical operators like AND, OR, and NOT?

a)

Resolution

b)

First order logic

c)

Predicate logic

d)

Propositional logic

2.

Which logic allows for the use of variables and quantifiers to represent relationships between objects?

a)

Propositional logic

b)

Predicate logic

c)

Resolution

d)

First order logic

3.

What is the process of deriving new information from known information in first order logic?

a)

Clause form conversion

b)

Resolution

c)

Inference

d)

Chaining

4.

Which concept involves a series of logical implications to reach a conclusion?

a)

Propositional logic

b)

Chaining

c)

Resolution

d)

Predicate logic

5.

What is the name of the reasoning process that starts with known facts and works towards a goal?

a)

Utility theory

b)

Probabilistic reasoning

c)

Forward chaining

d)

Backward chaining

6.

Which model is used to represent uncertain knowledge and make decisions under uncertainty?

a)

EM algorithm

b)

Reinforcement learning

c)

Naïve Bayes model

d)

Hidden Markov model

7.

What is the name of the model that assumes independence between features when making predictions?

a)

Hidden Markov model

b)

Reinforcement learning

c)

Naïve Bayes model

d)

EM algorithm

8.

What is the concept of learning when some of the data is not observed during the training process?

a)

Learning with hidden data

b)

Inference

c)

Naïve Bayes model

d)

Reinforcement learning

9.

Which algorithm is used to estimate the parameters of a statistical model with hidden variables?

a)

Reinforcement learning

b)

EM algorithm

c)

Naïve Bayes model

d)

Learning with hidden data

10.

What is the name of the learning process that involves taking actions to maximize rewards in a given environment?

a)

EM algorithm

b)

Reinforcement learning

c)

Learning with hidden data

d)

Naïve Bayes model

11.

Which field of study involves the recognition of patterns and regularities in data?

a)

Pattern Recognition

b)

Machine Learning

c)

Probabilistic reasoning

d)

Knowledge Representation and Reasoning

12.

What is the name of the model that uses observed data to make predictions based on probability?

a)

Hidden Markov model

b)

Naïve Bayes model

c)

EM algorithm

d)

Reinforcement learning

13.

What is the name of the model that uses observed data to make predictions based on probability?

a)

EM algorithm

b)

Reinforcement learning

c)

Naïve Bayes model

d)

Hidden Markov model

14.

What is the name of the model that uses observed data to make predictions based on probability?

a)

Reinforcement learning

b)

Hidden Markov model

c)

Naïve Bayes model

d)

EM algorithm

15.

What is the name of the model that uses observed data to make predictions based on probability?

a)

Reinforcement learning

b)

EM algorithm

c)

Naïve Bayes model

d)

Hidden Markov model

16.

What is the process of finding hidden patterns and regularities in data?

a)

Probabilistic reasoning

b)

Machine Learning

c)

Pattern Recognition

d)

Knowledge Representation and Reasoning

17.

Which algorithm is used to estimate the parameters of a statistical model with unobserved variables?

a)

Reinforcement learning

b)

Expectation-Maximization (EM) algorithm

c)

Naïve Bayes model

d)

Learning with hidden data

18.

What is the name of the reasoning process that starts with a goal and works towards known facts?

a)

Utility theory

b)

Probabilistic reasoning

c)

Backward chaining

d)

Forward chaining

19.

What is the process of finding hidden patterns and regularities in data?

a)

Probabilistic reasoning

b)

Machine Learning

c)

Pattern Recognition

d)

Knowledge Representation and Reasoning

20.

Which field of study involves the recognition of patterns and regularities in data?

a)

Pattern Recognition

b)

Machine Learning

c)

Probabilistic reasoning

d)

Knowledge Representation and Reasoning