Question 1

Which algorithm is used for solving temporal probabilistic reasoning?
A)hill-climbing search
B)hidden markov model
C)depth-first search
D)breadth-first search

Accepted Answer

Hidden Markov Model (HMM) is used for solving temporal probabilistic reasoning, as it is designed to work with sequences of events or states where the probabilities of certain outcomes are influenced by preceding events.

Question 2

How does the state of the process is described in HMM?
A)literal
B)single random variable
C)single discrete random variable
D)none of the mentioned

Accepted Answer

In a Hidden Markov Model (HMM), the state of the process is described as a single discrete random variable. This reflects the model's reliance on discrete states to represent the underlying process being modeled.

Question 3

What are the possible values of the variable?
A)variables
B)literals
C)discrete variable
D)possible states of the world

Accepted Answer

The possible states of the world are the different values that a variable can take on.

Question 4

Where does the additional variables are added in HMM?
A)temporal model
B)reality moddel
C)probability model
D)all of the mentioned

Accepted Answer

The answer of Where does the additional variables are added...

Question 5

Where does the Hidden Markov Model is used?
A)speech recognition
B)understanding of real world
C)both a & b
D)none of the mentioned

Accepted Answer

The answer of Where does the Hidden Markov Model is...

Question 6

Which algorithm works by first running the standard forward pass to compute?
A)smoothing
B)modified smoothing
C)hmm
D)depth-first search algorithm

Accepted Answer

The answer of Which algorithm works by first running the...

Question 7

Which reveals an improvement in online smoothing?
A)matrix formulation
B)revelation
C)hmm
D)none of the mentioned

Accepted Answer

Matrix formulation is known for improving the efficiency and effectiveness of online smoothing algorithms by providing a structured and scalable approach to handle large datasets and complex models.

Question 8

Where does the additional variable is added in HMM?
A)temporal model
B)reality model
C)probability model
D)all of the mentioned

Accepted Answer

The answer of Where does the additional variable is added...

Question 9

Which allows for a simple and matrix implementation of the entire basic algorithm?
A)hmm
B)restricted structure of hmm
C)temporary model
D)reality model

Accepted Answer

The restricted structure of Hidden Markov Models (HMMs) allows for a simple and matrix implementation of the entire basic algorithm. This structure simplifies the computations involved in the algorithms used for training and inference in HMMs.

Question 10

Which variable can give the concrete form to the representation of the transition model?
A)single variable
B)discrete state variable
C)random variable
D)both a & b

Accepted Answer

The transition model in many contexts, especially in artificial intelligence and decision-making processes, can be effectively represented using both single variables and discrete state variables. Single variables can represent specific states or decisions, while discrete state variables can represent a range of states or outcomes, making them both suitable for giving concrete form to transition models.

Question 11

Which suggests the existence of efficient recursive algorithm for online smoothing?
A)matrix
B)constant space
C)constant time
D)none of the mentioned

Accepted Answer

Constant space suggests the existence of an efficient recursive algorithm for online smoothing because it implies that the algorithm can operate with a fixed amount of memory, regardless of the input size, making it suitable for online (real-time) processing.

Question 12

Which algorithm is in more similar to backward chaining algorithm?
A)depth-first search algorithm
B)breadth-first search algorithm
C)hill-climbing search algorithm
D)all of the mentioned

Accepted Answer

Backward chaining is a form of reasoning that starts with the goal and works backwards to deduce the facts or actions needed to reach the goal. This approach is similar to the depth-first search algorithm, which explores as far as possible along each branch before backtracking.

Question 13

Which of the following search belongs to totally ordered plan search?
A)forward state-space search
B)hill-climbing search
C)depth-first search
D)breadth-first search

Accepted Answer

Forward state-space search is a type of totally ordered plan search where actions are applied in a sequence from the initial state to reach the goal state.

Question 14

Which cannot be taken as advantage for totally ordered plan search?
A)composition
B)state search
C)problem decomposition
D)none of the mentioned

Accepted Answer

The answer of Which cannot be taken as advantage for...

Question 15

What is the advantage of totally ordered plan in constructing the plan?
A)reliability
B)flexibility
C)easy to use
D)all of the mentioned

Accepted Answer

The answer of What is the advantage of totally ordered...

Question 16

Which strategy is used for delaying a choice during search?
A)first commitment
B)least commitment
C)both a & b
D)none of the mentioned

Accepted Answer

The least commitment strategy is used for delaying a choice during search, allowing for more flexibility in decision-making by not committing to a specific path too early.

Question 17

Which algorithm place two actions into a plan without specifying which should come first?
A)full-order planner
B)total-order planner
C)semi-order planner
D)partial-order planner

Accepted Answer

Partial-order planning allows for the inclusion of actions in a plan without specifying a strict sequence for their execution, unless required by the plan's constraints. This flexibility enables more efficient planning in complex scenarios.

Question 18

How many possible plans are available in partial-order solution?
A)3
B)4
C)5
D)6

Accepted Answer

Partial-order planning, a type of automated planning in artificial intelligence, allows for a flexible ordering of actions. It doesn't commit to an exact sequence of actions unless necessary, leading to multiple possible plans. The exact number of plans depends on the specific problem and constraints, but in general, there can be more than 6 possible plans, making D the closest choice given the options.

Question 19

What is the other name of each and every total-order plans?
A)polarization
B)linearization
C)solarization
D)none of the mentioned

Accepted Answer

Total-order plans are also known as linearization because they involve arranging actions in a single, linear sequence where each action must be completed before the next one begins.

Question 20

What is the study of light?
A)biology
B)light logy
C)photometry
D)all of the mentioned

Accepted Answer

Photometry is the science of the measurement of light, in terms of its perceived brightness to the human eye. It is distinct from radiometry, which is the science of measurement of radiant energy (including light) in terms of absolute power. Neither biology, which is the study of living organisms, nor "light logy," which is not a recognized field of study, pertains to the study of light specifically.

Quiz 1: Algorithms and Logic in Probabilistic Reasoning and Planning

Which algorithm is used for solving temporal probabilistic reasoning?

How does the state of the process is described in HMM?

What are the possible values of the variable?

Where does the additional variables are added in HMM?

Where does the Hidden Markov Model is used?

Which algorithm works by first running the standard forward pass to compute?

Which reveals an improvement in online smoothing?

Where does the additional variable is added in HMM?

Which allows for a simple and matrix implementation of the entire basic algorithm?

Which variable can give the concrete form to the representation of the transition model?

Which suggests the existence of efficient recursive algorithm for online smoothing?

Which algorithm is in more similar to backward chaining algorithm?

Which of the following search belongs to totally ordered plan search?

Which cannot be taken as advantage for totally ordered plan search?

What is the advantage of totally ordered plan in constructing the plan?

Which strategy is used for delaying a choice during search?

Which algorithm place two actions into a plan without specifying which should come first?

How many possible plans are available in partial-order solution?

What is the other name of each and every total-order plans?

What is the study of light?