---
title: "Explain the minimax algorithm in different terms in AI."  
description: "Explain the minimax algorithm in different terms in AI."  
author: "Sandra Emily"  
published: 2024-04-05  
updated: 2024-05-15  
canonical: https://www.mindstick.com/forum/160612/explain-the-minimax-algorithm-in-different-terms-in-ai  
category: "artificial intelligence"  
tags: ["algorithm", "artificial intelligence", "ai", "minimax algorithm"]  
reading_time: 2 minutes  

---

# Explain the minimax algorithm in different terms in AI.

[Explain](https://www.mindstick.com/forum/157854/what-is-system-debugging-explain-some-system-debugging-tools-used-in-modern-computer-systems) the minimax [algorithm](https://www.mindstick.com/blog/119/implementing-cryptography-in-c-sharp-dot-net-by-using-sha1-algorithm) in different terms.

## Replies

### Reply by Bhavesh Badani

#### Minimax Algorithm:

1. Game theory uses a decision-making process called minimax.

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2. Assuming that the other player plays optimally as well, it aids in determining the best move for the player.

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3. frequently employed in two-player turn-based games such as Backgammon, Chess, and Tic-Tac-Toe.

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4. The maximizer and the minimizer are the two participants in Minimax.

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5. While the minimizer seeks to obtain the lowest score, the maximizer seeks to obtain the best score.

#### States and Values of the Board:

Every board state has a corresponding value. \
The score is often negative when the minimizer has the upper hand and positive when the maximizer is in the lead. \
Heuristics unique to each game are used to compute these values.

## Example:

- Imagine a game with 4 final states represented by a perfect binary tree.
- As the maximizing player, you start at the root, and your opponent is at the next level.
- Minimax explores all possible moves and backtracks to make a decision.
- Always assume the opponent plays optimally.
- The optimal move is chosen based on the highest or lowest value


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