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

called Yao's minimax principle or Yao's lemma) relates the performance of randomized algorithms to deterministic (non-random) algorithms. It states that...

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...

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 (...

artificial intelligence. Examples of algorithms for this class are the minimax algorithm, alpha–beta pruning, and the A* algorithm and its variants. An important...

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

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

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

coalition. The paranoid algorithm significantly improves upon the maxn algorithm by enabling the use of alpha-beta pruning and other minimax-based optimization...

method: 2-point, 1-sided Hybrid Algorithms Alpha–beta pruning: search to reduce number of nodes in minimax algorithm A hybrid BFGS-Like method (see more...

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...

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...

gradient descent Local search (Texel tuning) Graph and tree search algorithms Minimax Alpha-beta pruning Principal variation search Quiescence search Monte...

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

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

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...

or not each candidate satisfies the problem's statement. A brute-force algorithm that finds the divisors of a natural number n would enumerate all integers...

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...

programs, but still quite good.[citation needed] KnightCap's home page KnightCap: A Chess program that learns by combining TD(λ) with minimax search...

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...

In statistical decision theory, a minimax estimator δ M {\displaystyle \delta ^{M}\,\!} is an estimator which performs best in the worst possible case...

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...

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...

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...

is a minimax search algorithm developed in 2011 that optimizes decision-making in game trees. BNS differentiates itself from traditional algorithms by identifying...

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

in power systems. Measuring homogeneity of two-dimensional materials. Minimax process control. Minimum spanning trees can also be used to describe financial...

gradient descent Local search (Texel tuning) Graph and tree search algorithms Minimax Alpha-beta pruning Principal variation search Quiescence search Monte...

gradient descent Local search (Texel tuning) Graph and tree search algorithms Minimax Alpha-beta pruning Principal variation search Quiescence search Monte...