Question 1

A _________ is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility.

Accepted Answer

A decision tree is a decision support tool that visually maps out decisions and their potential consequences, making it easier to analyze and come to a decision.

Question 2

Decision Tree is

Accepted Answer

A decision tree is indeed a flow-chart-like structure where each internal node represents a test on an attribute, each branch represents the outcome of that test, and each leaf node represents a class label (decision taken after computing all attributes).

Question 3

How many types of learning are available in machine learning?

Accepted Answer

There are three primary types of learning in machine learning: supervised learning, unsupervised learning, and reinforcement learning.

Question 4

Choose from the following that are Decision Tree nodes

Accepted Answer

The answer of Choose from the following that are Decision...

Question 5

Decision Nodes are represented by,

Accepted Answer

Decision nodes are typically represented by squares in decision tree diagrams, indicating points where a decision must be made.

Question 6

Chance Nodes are represented by,

Accepted Answer

Chance nodes in decision trees and similar diagrams are typically represented by circles. These nodes are used to indicate points where a random outcome will occur.

Question 7

End Nodes are represented by,

Accepted Answer

The answer of End Nodes are represented by,
...

Question 8

How the decision tree reaches its decision?

Accepted Answer

Decision trees reach their decisions through a sequence of tests, where each node in the tree represents a test on an attribute, and each branch represents the outcome of the test, leading to further tests or a decision.

Question 9

What is the other name of informed search strategy?

Accepted Answer

The other name for an informed search strategy is heuristic search, as it uses additional information (or heuristics) to guide the search process towards the goal more efficiently than an uninformed search strategy, which does not have such guidance.

Question 10

How many types of informed search method are in artificial intelligence?

Accepted Answer

In artificial intelligence, there are four primary types of informed search methods: Best-first search, A* search, Greedy search, and Hill-climbing search. Each of these methods uses knowledge beyond the problem definition itself to find solutions more efficiently than uninformed search methods.

Question 11

Which function will select the lowest expansion node atfirst for evaluation?

Accepted Answer

The answer of Which function will select the lowest expansion...

Question 12

What is the heuristic function of greedy best-first search?

Accepted Answer

The heuristic function of greedy best-first search is defined as f(n) = h(n), where h(n) is the estimated cost from node n to the goal. This heuristic guides the search process towards the goal by prioritizing nodes that are believed to be closer to the goal.

Question 13

Which search uses only the linear space for searching?

Accepted Answer

The answer of Which search uses only the linear space...

Question 14

Which method is used to search better by learning?

Accepted Answer

Metalevel state space is used to search better by incorporating learning into the search process. This approach involves reasoning about the strategies to apply in the search process itself, potentially improving the efficiency and effectiveness of the search.

Question 15

Which search is complete and optimal when h(n) is consistent?

Accepted Answer

A* search is complete and optimal when the heuristic function h(n) is consistent (or monotonic), ensuring that it always finds the least cost path to the goal if one exists.

Question 16

Which is used to improve the performance of heuristic search?

Accepted Answer

The quality of the heuristic function directly impacts the efficiency and performance of heuristic search algorithms by providing a more accurate estimate of the cost to reach the goal, thus leading to a more informed search process.

Question 17

Which search method will expand the node that is closest to the goal?

Accepted Answer

Greedy best-first search expands the node that is closest to the goal, as it uses a heuristic to estimate how close each node is to the goal and chooses the node that appears to be closest.

Question 18

Which data structure is used to give better heuristic estimates?

Accepted Answer

The planning graph algorithm is used to give better heuristic estimates by structuring the problem in a way that allows for more efficient analysis of possible actions and their outcomes.

Question 19

Which is used to extract solution directly from the planning graph?

Accepted Answer

GraphPlan is specifically designed to extract solutions directly from a planning graph, which is a graphical representation of a planning problem.

Question 20

What are present in the planning graph?

Accepted Answer

A planning graph is a sequence of levels, each consisting of a set of actions and a set of literals that represent the possible states of the world at that level.

Quiz 3: Decision Trees, Machine Learning, and Heuristic Search in Artificial Intelligence