Data structures and other details about minimax algorithm

  • How does the minimax algorithm use game theory to determine the optimal move in a two-player game?

    For two player games, the minimax algorithm is such a tactic, which uses the fact that the two players are working towards opposite goals to make predictions about which future states will be reached as the game progresses, and then proceeds accordingly to optimize its chance of victory..

  • How does the 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)..

  • What are the properties of minimax algorithm?

    Properties of Mini-Max algorithm:
    Optimal- Min-Max algorithm is optimal if both opponents are playing optimally.
    Time complexity- As it performs DFS for the game-tree, so the time complexity of Min-Max algorithm is O(bm), where b is branching factor of the game-tree, and m is the maximum depth of the tree..

  • What is the minimax algorithm based on?

    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.Jun 13, 2022.

  • What is the working principle of minimax algorithm?

    The Minimax Algorithm

    1. The algorithm performs what we call a “depth-first search” in computer science
    2. The Minimax Algorithm moves in depth-first fashion down the tree until it reaches a terminal node (i
      3. .e. someone wins the game) or a pre-determined depth limit.

  • Which data structure is used for minimax algorithm?

    The algorithm looks ahead at all the possible values till the end and makes a decision for the player.
    The game tree above is a nested data structure that is used to evaluate the moves.
    Here the root node is Level 0, which branches out into Level 1 or parent nodes, which further branch out into Level 2 or child nodes.Dec 21, 2020.

  • Minimax algorithm assumption
    When running the minimax algorithm, it is assumed that your opponent is playing optimally.
    This assumption is a worst case scenario, given that if your opponent is not playing optimally the problem is reduced to a simpler one.
  • The expectiminimax algorithm is a variation of the minimax algorithm, for use in artificial intelligence systems that play two-player zero-sum games, such as backgammon, in which the outcome depends on a combination of the player's skill and chance elements such as dice rolls.
  • The MiniMax algorithm conducts a depth-first search to explore the complete game tree and then proceeds down to the leaf node of the tree, then backtracks the tree using recursive calls.
    To better understand, let us consider an example of tic-tac-toe, a two-player game in which each player plays turn by turn.
The Min Max algorithm recursively evaluates all possible moves the current player and the opponent player can make. It starts at the root of the game tree and applies the MinMax algorithm to each child node. At each level of the tree, the algorithm alternates between maximizing and minimizing the node's value.
The Min Max algorithm recursively evaluates all possible moves the current player and the opponent player can make. It starts at the root of the game tree and applies the MinMax algorithm to each child node. At each level of the tree, the algorithm alternates between maximizing and minimizing the node's value.
This Algorithm computes the minimax decision for the current state. In this algorithm two players play the game, one is called MAX and other is called MIN. Both 

How does minimax work?

Having understood the basic functionality of the algorithm, let us put it in more formal terms

Minimax, by its nature, is a depth-first search and can be conveniently coded as a recursive function

The procedure is summarized in the following pseudocode: All nodes of the state tree must be accessed at least once

What is a minimax algorithm?

An analog thing happens to minimize

The -/+ infinity in the decision function (first call to maximize) means that we begin the algorithm with no restriction on what the resulting score can be

So, the minimax algorithm is a relatively easy algorithm that works well on simple games (low branching factor)

What is alpha-beta pruning in a minimax algorithm?

When using alpha-beta pruning in a minimax algorithm, it is needed to track the value of two different variables (alpha and beta) in order to decide when to prune a part of the tree

At the beginning of the game, alpha is equal to negative infinity and beta is equal to positive infinity

These values are updated as the game progresses


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