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- Expectiminimax_tree abstract "An expectiminimax tree is a specialized variation of a minimax game tree for use in artificial intelligence systems that play two-player zero-sum games such as backgammon, in which the outcome depends on a combination of the player's skill and chance elements such as dice rolls. In addition to "min" and "max" nodes of the traditional minimax tree, this variant has "chance" ("move by nature") nodes, which take the expected value of a random event occurring. In game theory terms, an expectiminimax tree is the game tree of an extensive-form game of perfect, but incomplete information.In the traditional minimax method, the levels of the tree alternate from max to min until the depth limit of the tree has been reached. In an expectiminimax tree, the "chance" nodes are interleaved with the max and min nodes. Instead of taking the max or min of the utility values of their children, chance nodes take a weighted average, with the weight being the probability that that child is reached.The interleaving depends on the game. Each "turn" of the game is evaluated as a "max" node (representing the AI player's turn), a "min" node (representing a potentially-optimal opponent's turn), or a "chance" node (representing a random effect or player).For example, consider a game which, in each round, consists of a single dice throw, and then decisions made by first the AI player, and then another intelligent opponent. The order of nodes in this game would alternate between "chance", "max" and then "min".".
- Expectiminimax_tree wikiPageID "1153192".
- Expectiminimax_tree wikiPageRevisionID "543881775".
- Expectiminimax_tree hasPhotoCollection Expectiminimax_tree.
- Expectiminimax_tree subject Category:Game_artificial_intelligence.
- Expectiminimax_tree subject Category:Game_theory.
- Expectiminimax_tree subject Category:Search_algorithms.
- Expectiminimax_tree subject Category:Trees_(data_structures).
- Expectiminimax_tree type Abstraction100002137.
- Expectiminimax_tree type Act100030358.
- Expectiminimax_tree type Activity100407535.
- Expectiminimax_tree type Algorithm105847438.
- Expectiminimax_tree type Event100029378.
- Expectiminimax_tree type Procedure101023820.
- Expectiminimax_tree type PsychologicalFeature100023100.
- Expectiminimax_tree type Rule105846932.
- Expectiminimax_tree type SearchAlgorithms.
- Expectiminimax_tree type YagoPermanentlyLocatedEntity.
- Expectiminimax_tree comment "An expectiminimax tree is a specialized variation of a minimax game tree for use in artificial intelligence systems that play two-player zero-sum games such as backgammon, in which the outcome depends on a combination of the player's skill and chance elements such as dice rolls. In addition to "min" and "max" nodes of the traditional minimax tree, this variant has "chance" ("move by nature") nodes, which take the expected value of a random event occurring.".
- Expectiminimax_tree label "Expectiminimax tree".
- Expectiminimax_tree label "Expectiminimax-Algorithmus".
- Expectiminimax_tree sameAs Expectiminimax-Algorithmus.
- Expectiminimax_tree sameAs m.04btf_.
- Expectiminimax_tree sameAs Q1384259.
- Expectiminimax_tree sameAs Q1384259.
- Expectiminimax_tree sameAs Expectiminimax_tree.
- Expectiminimax_tree wasDerivedFrom Expectiminimax_tree?oldid=543881775.
- Expectiminimax_tree isPrimaryTopicOf Expectiminimax_tree.