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Minimax Algorithm and Alpha-Beta Pruning

Authored by Yosi Kristian

Computers

Used 16+ times

Minimax Algorithm and Alpha-Beta Pruning
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12 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

In which type of games is the Minimax algorithm commonly used?

Cooperative games

Zero-sum games

Single-player puzzle games

Real-time strategy games

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What does Alpha-Beta Pruning help to reduce in the Minimax algorithm?

The number of nodes evaluated

The depth of the search tree

The algorithm's complexity

The memory usage

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How does the Alpha-Beta Pruning algorithm decide whether to prune a branch or not?

Based on the depth of the branch

Based on the comparison between alpha and beta values

Based on the number of nodes in the branch

Based on the time elapsed since the search started

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What does the term 'branching factor' refer to in a game tree?

The number of possible moves from a given game state

The depth of the tree

The total number of nodes

The number of terminal nodes

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the main drawback of the basic Minimax algorithm?

It requires human intervention.

It is too fast and skips important calculations.

It can be computationally expensive for large trees.

It is too simple for any practical use.

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

In the context of adversarial search, what is a 'utility function'?

A function that generates random moves

A function that calculates the desirability of a states in a game tree with limited depth

A function that connects to a utility server

A function that minimizes utility costs

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How does Alpha-Beta Pruning improve the efficiency of the Minimax algorithm?

By using less memory

By eliminating the need for a search tree

By skipping the evaluation of certain branches

By reducing the number of players in the game

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