Search results
Results from the WOW.Com Content Network
For example, given a function ... One popular minimax approximation algorithm is the Remez algorithm. References External links. Minimax approximation algorithm at ...
For example, the ML estimator from the previous example may be attained as the limit of Bayes estimators with respect to a uniform prior, [,] with increasing support and also with respect to a zero-mean normal prior (,) with increasing variance. So neither the resulting ML estimator is unique minimax nor the least favorable prior is unique.
Bruce Ballard was the first to develop a technique, called *-minimax, that enables alpha-beta pruning in expectiminimax trees. [3] [4] The problem with integrating alpha-beta pruning into the expectiminimax algorithm is that the scores of a chance node's children may exceed the alpha or beta bound of its parent, even if the weighted value of each child does not.
Sion's minimax theorem is a generalization of von Neumann's minimax theorem due to Maurice Sion, [6] relaxing the requirement that It states: [6] [7] Let X {\displaystyle X} be a convex subset of a linear topological space and let Y {\displaystyle Y} be a compact convex subset of a linear topological space .
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.). It stops evaluating a move when at least one ...
An animated pedagogical example showing the plain negamax algorithm (that is, without alpha–beta pruning). The person performing the game tree search is considered to be the one that has to move first from the current state of the game (player in this case) NegaMax operates on the same game trees as those used with the minimax search ...
Yao's principle extends lower bounds for the average case number of comparisons made by deterministic algorithms, for random permutations, to the worst case analysis of randomized comparison algorithms. [2] An example given by Yao is the analysis of algorithms for finding the th largest of a given set of values, the selection problem. [2]
In decision theory and game theory, Wald's maximin model is a non-probabilistic decision-making model according to which decisions are ranked on the basis of their worst-case outcomes – the optimal decision is one with the least bad outcome.