How the mini max algorithm is used in decision making and game theory?

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. The minimax algorithm performs a depth-first search algorithm for the exploration of the complete game tree.

What type of algorithm is minimax?

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.

Why does the minimax algorithm is termed as minimax?

The name minimax arises because each player minimizes the maximum payoff possible for the other—since the game is zero-sum, they also minimize their own maximum loss (i.e. maximize their minimum payoff).

What is minimax and Maximin principle in game theory?

zero-sum game: A zero-sum game is one in which the sum of the individual payoffs for each outcome is zero. Minimax strategy: minimizing one’s own maximum loss. Maximin strategy: maximize one’s own minimum gain.

How is minimax strategy used in games explain the strategy on the basis of game playing?

In game theory, minimax is a decision rule used to minimize the worst-case potential loss; in other words, a player considers all of the best opponent responses to his strategies, and selects the strategy such that the opponent’s best strategy gives a payoff as large as possible.

What is minimax criterion in decision making?

Min-max criterion – is a decision-making criterion presented in 1954 by Leonard Savage. This criterion minimizes the expected loss associated with making worse than optimal decision, for a given state of nature.

How do you make a Minimax algorithm?

3. Minimax Algorithm

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

What happens when maximin and minimax values are the same Mcq?

If the maximin value equals the minimax value, then the game is said to have a saddle (equilibrium) point and the corresponding strategies are called optimum stratagies. The amount of payoff at an equilibrium point is known as the value of the game.

What is minimax criterion in decision-making?

What happens when maximin and minimax value of game are same?

What is the minimax regret decision?

The minimax regret strategy is the one that minimises the maximum regret. It is useful for a risk-neutral decision maker. Essentially, this is the technique for a ‘sore loser’ who does not wish to make the wrong decision.