Minimax (sometimes Minmax, MM or saddle point) is a decision rule used in artificial intelligence, decision theory, game theory, statistics, and philosophy...

A minimax approximation algorithm (or L∞ approximation or uniform approximation) is a method to find an approximation of a mathematical function that...

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...

artificial intelligence. Examples of algorithms for this class are the minimax algorithm, alpha–beta pruning, and the A* algorithm and its variants. The name "combinatorial...

Negamax search is a variant form of minimax search that relies on the zero-sum property of a two-player game. This algorithm relies on the fact that ⁠ min (...

refer to: Minimax estimator, an estimator whose maximal risk is minimal between all possible estimators Minimax approximation algorithm, algorithms to approximate...

In statistics, the k-nearest neighbors algorithm (k-NN) is a non-parametric supervised learning method first developed by Evelyn Fix and Joseph Hodges...

Hybrid Algorithms Alpha–beta pruning: search to reduce number of nodes in minimax algorithm Branch and bound Bruss algorithm: see odds algorithm Chain...

(also called Yao's minimax principle or Yao's lemma) is a way to prove lower bounds on the worst-case performance of randomized algorithms, by comparing them...

transportation planning. Any algorithm for the widest path problem can be transformed into an algorithm for the minimax path problem, or vice versa, by...

the two faces do not overlap (minimax test in X) The extreme coordinate values in Y of the two faces do not overlap (minimax test in Y) All vertices of P...

The expectiminimax algorithm is a variation of the minimax algorithm, for use in artificial intelligence systems that play two-player zero-sum games,...

estimator (estimation rule) δ M {\displaystyle \delta ^{M}\,\!} is called minimax if its maximal risk is minimal among all estimators of θ {\displaystyle...

analyzed under the conditions of worst and average case and in the sense of a minimax value of a zero-sum game in game theory. With four holes and six colors...

God's number, or, more formally, the minimax value. God's algorithm, then, for a given puzzle, is an algorithm that solves the puzzle and produces only...

best approximation or the minimax approximation algorithm. A review of technicalities in implementing the Remez algorithm is given by W. Fraser. The...

research company DeepMind to master the games of chess, shogi and go. This algorithm uses an approach similar to AlphaGo Zero. On December 5, 2017, the DeepMind...

(1953) as a minimax search for the maximum (minimum) of a unimodal function in an interval. The Bisection method is a similar algorithm for finding a...

child of parent(J) to OPEN Roizen, Igor; Judea Pearl (March 1983). "A minimax algorithm better than alpha–beta?: Yes and No". Artificial Intelligence. 21...

S Li (2020). "Improving Generalization of Reinforcement Learning with Minimax Distributional Soft Actor-Critic". 2020 IEEE 23rd International Conference...

Deep Blue used custom VLSI chips to parallelize the alpha–beta search algorithm, an example of symbolic AI. The system derived its playing strength mainly...

learning Texel tuning Unsupervised learning Graph and tree search algorithms Minimax Alpha-beta pruning Principal variation search Quiescence search Monte...

performance in go, chess, shogi, and a standard suite of Atari games. The algorithm uses an approach similar to AlphaZero. It matched AlphaZero's performance...

Quiescence search is an algorithm typically used to extend search at unstable nodes in minimax game trees in game-playing computer programs. It is an extension...

as Minimax) can fail the Smith criterion. Mutual majority criterion#Minimax The Smith criterion implies the mutual majority criterion, so Minimax's failure...

doi:10.1016/0377-2217(95)90075-6. Jacobsen, S. K. (1981), "An algorithm for the minimax Weber problem", European Journal of Operational Research, 6 (2):...

learning Texel tuning Unsupervised learning Graph and tree search algorithms Minimax Alpha-beta pruning Principal variation search Quiescence search Monte...

then makes the move with the highest resulting points, employing a minimax algorithm to do so. Points are determined based on several criteria, such as...

which is not Condorcet-consistent must also fail the Smith criterion. Minimax is the most well-known Condorcet method that fails the Smith criterion;...

position on the board. This search process is called minimax. A naive implementation of the minimax algorithm can only search to a small depth in a practical...