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O que (quem) é minimax principle - definição

DECISION RULE USED IN ARTIFICIAL INTELLIGENCE, DECISION THEORY, GAME THEORY, STATISTICS AND PHILOSOPHY FOR MINIMIZING THE POSSIBLE LOSS FOR A WORST CASE (MAXIMUM LOSS) SCENARIO

Minimax algorithm; Minimax test; Maximin principle; Maximin criterion; Minmax; Maximin (decision theory); Bottleneck programming; Minimax strategy; Game value; Maximin (philosophy); Minimax principle; Maxmin; MiniMax; Minimax Strategy; Minimax solution; Minmax algorithm; Maximin Principle

Yao's principle

Yao Principle; Yao's Principle; Yao's minimax principle

In computational complexity theory, Yao's principle (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 to deterministic (non-random) algorithms. It states that, for any randomized algorithm, there exists a probability distribution on inputs to the algorithm, so that the expected cost of the randomized algorithm on its worst-case input is at least as large as the cost of the best deterministic algorithm on a random input from this distribution.

https://en.wikipedia.org/wiki/Yao's_principle

Courant minimax principle

Courant minimax

In mathematics, the Courant minimax principle gives the eigenvalues of a real symmetric matrix. It is named after Richard Courant.

https://en.wikipedia.org/wiki/Courant_minimax_principle

Minimax theorem

THEOREM PROVIDING CONDITIONS THAT GUARANTEE THAT THE MAX–MIN INEQUALITY IS ALSO AN EQUALITY

Von Neumman's minimax theorem

In the mathematical area of game theory, a minimax theorem is a theorem providing conditions that guarantee that the max–min inequality is also an equality.

https://en.wikipedia.org/wiki/Minimax_theorem

Wikipédia

Minimax

Minimax (sometimes MinMax, MM or saddle point) is a decision rule used in artificial intelligence, decision theory, game theory, statistics, and philosophy for minimizing the possible loss for a worst case (maximum loss) scenario. When dealing with gains, it is referred to as "maximin" – to maximize the minimum gain. Originally formulated for several-player zero-sum game theory, covering both the cases where players take alternate moves and those where they make simultaneous moves, it has also been extended to more complex games and to general decision-making in the presence of uncertainty.

https://en.wikipedia.org/wiki/Minimax