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  2. Expectiminimax - Wikipedia

    en.wikipedia.org/wiki/Expectiminimax

    The interleaving depends on the game. Each "turn" of the game is evaluated as a "max" node (representing the AI player's turn), a "min" node (representing a potentially-optimal opponent's turn), or a "chance" node (representing a random effect or player). [1] For example, consider a game in which each round consists of a single die throw, and ...

  3. Alpha–beta pruning - Wikipedia

    en.wikipedia.org/wiki/Alpha–beta_pruning

    Alpha–beta pruning is a search algorithm that seeks to decrease the number of nodes that are evaluated by the minimax algorithm in its search tree.It is an adversarial search algorithm used commonly for machine playing of two-player combinatorial games (Tic-tac-toe, Chess, Connect 4, etc.).

  4. Feature scaling - Wikipedia

    en.wikipedia.org/wiki/Feature_scaling

    Also known as min-max scaling or min-max normalization, rescaling is the simplest method and consists in rescaling the range of features to scale the range in [0, 1] or [−1, 1]. Selecting the target range depends on the nature of the data. The general formula for a min-max of [0, 1] is given as: [3]

  5. Minimax approximation algorithm - Wikipedia

    en.wikipedia.org/.../Minimax_approximation_algorithm

    For example , given a function ... , a minimax polynomial approximation algorithm will find a ... For practical work it is often desirable to minimize the maximum ...

  6. Minimax estimator - Wikipedia

    en.wikipedia.org/wiki/Minimax_estimator

    Example 3: Bounded normal mean: When estimating the mean of a normal vector (,), where it is known that ‖ ‖. The Bayes estimator with respect to a prior which is uniformly distributed on the edge of the bounding sphere is known to be minimax whenever M ≤ n {\displaystyle M\leq n\,\!} .

  7. Game tree - Wikipedia

    en.wikipedia.org/wiki/Game_tree

    Randomized algorithms can be used in solving game trees. There are two main advantages in this type of implementation: speed and practicality. Whereas a deterministic version of solving game trees can be done in Ο(n), the following randomized algorithm has an expected run time of θ(n 0.792) if every node in the game tree has degree 2 ...

  8. Negamax - Wikipedia

    en.wikipedia.org/wiki/Negamax

    This is a coding simplification over minimax, which requires that A selects the move with the maximum-valued successor while B selects the move with the minimum-valued successor. It should not be confused with negascout , an algorithm to compute the minimax or negamax value quickly by clever use of alpha–beta pruning discovered in the 1980s.

  9. Alpha max plus beta min algorithm - Wikipedia

    en.wikipedia.org/wiki/Alpha_max_plus_beta_min...

    The algorithm avoids performing the square and square-root operations, instead using simple operations such as comparison, multiplication, and addition. Some choices of the α and β parameters of the algorithm allow the multiplication operation to be reduced to a simple shift of binary digits that is particularly well suited to implementation ...