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Expectimax search

Technique

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About Expectiminimax · from Wikipedia

The expectiminimax algorithm is a variation of the minimax algorithm, 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" 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.

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  • 2048 solver Oct 2026
    Expectimax search. The solver alternates two kinds of step: your move: it takes the best of the four directions; the game's move: it averages over every empty cell receiving a 2 (90% chance) or a 4 (10% chance).

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Everything on this page is read from triples in the knowledge graph. These are the 4 it states about Expectimax search, and 1 more its ontology implies; the console runs SPARQL over the whole graph, here in your browser.

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@prefix id: <https://ask.chaipat.cc/id/> .
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix cj: <https://ask.chaipat.cc/ns#> .
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
@prefix skos: <http://www.w3.org/2004/02/skos/core#> .
@prefix schema: <https://schema.org/> .

id:Expectimax
    a cj:Technique ;
    rdfs:label "Expectimax search" ;
    skos:altLabel "expectimax" ;
    schema:sameAs <https://en.wikipedia.org/wiki/Expectiminimax> .
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