minimax criterion - definição. O que é minimax criterion. Significado, conceito
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O que (quem) é minimax criterion - 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
  • An animated pedagogical example that attempts to be human-friendly by substituting initial infinite (or arbitrarily large) values for emptiness and by avoiding using the [[negamax]] coding simplifications.

Minimax estimator         
  • left
Minimax Estimator; Minimax criterion; Least favorable prior; Least favourable prior
In statistical decision theory, where we are faced with the problem of estimating a deterministic parameter (vector) \theta \in \Theta from observations x \in \mathcal{X}, an estimator (estimation rule) \delta^M \,\! is called minimax if its maximal risk is minimal among all estimators of \theta \,\!.
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.
Jewish Criterion         
The Jewish Criterion; Jewish Criterion (Pittsburgh)
The Jewish Criterion (OCLC 2262915) whose editors included J. Leonard Levy (rabbi of Rodef Shalom) and Charles H.

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.