## What is minimax procedure explain with example?

Minimax is a kind of backtracking algorithm that is used in decision making and game theory to find the optimal move for a player, assuming that your opponent also plays optimally. It is widely used in two player turn-based games such as Tic-Tac-Toe, Backgammon, Mancala, Chess, etc.

**How do you write a minimax algorithm?**

3. Minimax Algorithm

- Construct the complete game tree.
- Evaluate scores for leaves using the evaluation function.
- Back-up scores from leaves to root, considering the player type: For max player, select the child with the maximum score.
- At the root node, choose the node with max value and perform the corresponding move.

**What is the minimax algorithm in AI?**

The min max algorithm in AI, popularly known as the minimax, is a backtracking algorithm used in decision making, game theory and artificial intelligence (AI). It is used to find the optimal move for a player, assuming that the opponent is also playing optimally.

### Which algorithm is used in tic-tac-toe?

Minimax Algorithm

Minimax Algorithm is a decision rule formulated for 2 player zero-sum games (Tic-Tac-Toe, Chess, Go, etc.). This algorithm sees a few steps ahead and puts itself in the shoes of its opponent.

**Which search method is used in minimax algorithm Mcq?**

Explanation: The minimax search is depth-first search, So at one time we just have to consider the nodes along a single path in the tree.

**How does a minimax algorithm work?**

The Minimax algorithm helps find the best move, by working backwards from the end of the game. At each step it assumes that player A is trying to maximize the chances of A winning, while on the next turn player B is trying to minimize the chances of A winning (i.e., to maximize B’s own chances of winning).

#### How does minimax algorithm work?

**What is minimax strategy?**

in game theory or decision making, a tactic in which individuals attempt either to minimize their own maximum losses or to reduce the most an opponent will gain.

**What is Minimax algorithm in tic-tac-toe?**

The key to the Minimax algorithm is a back and forth between the two players, where the player whose “turn it is” desires to pick the move with the maximum score. In turn, the scores for each of the available moves are determined by the opposing player deciding which of its available moves has the minimum score.

## Is tic-tac-toe discrete or continuous?

continuous game

A continuous game is a mathematical concept, used in game theory, that generalizes the idea of an ordinary game like tic-tac-toe (noughts and crosses) or checkers (draughts). In other words, it extends the notion of a discrete game, where the players choose from a finite set of pure strategies.

**What are the different search algorithms?**

Searching Algorithms :

- Linear Search.
- Binary Search.
- Jump Search.
- Interpolation Search.
- Exponential Search.
- Sublist Search (Search a linked list in another list)
- Fibonacci Search.
- The Ubiquitous Binary Search.

**What is Mini-Max algorithm?**

Mini-max algorithm is a recursive or backtracking algorithm which is used in decision-making and game theory. It provides an optimal move for the player assuming that opponent is also playing optimally. Mini-Max algorithm uses recursion to search through the game-tree. Min-Max algorithm is mostly used for game playing in AI.

### What does minimax mean in chess?

You would probably want to maximize your score and minimize your component’s score (which is also you, lol), hence the name Minimax. The same you do when you play for the other side, picking the action to maximize your score and minimize your opponent’s score.

**What is the difference between Minimax and Max?**

To do this it selects two players one is the min, and the other is max, the goal of min player is to pick the minimum value, and on the other hand, the goal of max is to pick the maximum value. What is the Minimax Algorithm? It is a decision-making algorithm used in game theory.

**What is the minimax decision rule?**

It is called the Minimax Decision Rule, which is a type of Adversarial Search, meaning that this algorithm faces an opponent that is playing against the machine.