Engineering Questions with Answers - Multiple Choice Questions

Home » MCQs » Engineering MCQs » Artificial Intelligence MCQ – Hidden Markov Model

# Artificial Intelligence MCQ – Hidden Markov Model

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

**
View Answer**

Answer: b

Explanation: Hidden Markov model is used for solving temporal probabilistic reasoning that was independent of transition and sensor model.

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

**
View Answer**

Answer: c

Explanation: An HMM is a temporal probabilistic model in which the state of the process is described by a single discrete random variable.

What are the possible values of the variable?

a) Variables

b) Literals

c) Discrete variable

d) Possible states of the world

**
View Answer**

Answer: d

Explanation: The possible values of the variables are the possible states of the world.

Where does the additional variables are added in HMM?

a) Temporal model

b) Reality model

c) Probability model

d) All of the mentioned

**
View Answer**

Answer: a

Explanation: Additional state variables can be added to a temporal model while staying within the HMM framework.

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

a) HMM

b) Restricted structure of HMM

c) Temporary model

d) Reality model

**
View Answer**

Answer: b

Explanation: Restricted structure of HMM allows for a very simple and elegant matrix implementation of all the basic algorithm.

Where does the Hidden Markov Model is used?

a) Speech recognition

b) Understanding of real world

c) Both Speech recognition & Understanding of real world

d) None of the mentioned

**
View Answer**

Answer: a

Explanation: None.

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 Single & Discrete state variable

**
View Answer**

Answer: d

Explanation: With a single, discrete state variable, we can give concrete form to the representation of the transition model.

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

a) Smoothing

b) Modified smoothing

c) HMM

d) Depth-first search algorithm

**
View Answer**

Answer: b

Explanation: The modified smoothing algorithm works by first running the standard forward pass to compute and then running the backward pass.

Which reveals an improvement in online smoothing?

a) Matrix formulation

b) Revelation

c) HMM

d) None of the mention ed

**
View Answer**

Answer: a

Explanation: Matrix formulation reveals an improvement in online smoothing with a fixed lag.

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

a) Matrix

b) Constant space

c) Constant time

d) None of the mentioned

**
View Answer**

Answer: b

Explanation: None.