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- Thompson_sampling abstract "In artificial intelligence, Thompson sampling, named after William R. Thompson, is a heuristic for choosing actions that addresses the exploration-exploitation dilemma in the multi-armed bandit problem. It consists in choosing the action that maximizes the expected reward with respect to a randomly drawn belief.".
- Thompson_sampling wikiPageID "34130293".
- Thompson_sampling wikiPageRevisionID "584877611".
- Thompson_sampling hasPhotoCollection Thompson_sampling.
- Thompson_sampling subject Category:Articles_created_via_the_Article_Wizard.
- Thompson_sampling subject Category:Artificial_intelligence.
- Thompson_sampling subject Category:Heuristic_algorithms.
- Thompson_sampling subject Category:Sequential_experiments.
- Thompson_sampling subject Category:Sequential_methods.
- Thompson_sampling type Abstraction100002137.
- Thompson_sampling type Act100030358.
- Thompson_sampling type Activity100407535.
- Thompson_sampling type Algorithm105847438.
- Thompson_sampling type Event100029378.
- Thompson_sampling type HeuristicAlgorithms.
- Thompson_sampling type Procedure101023820.
- Thompson_sampling type PsychologicalFeature100023100.
- Thompson_sampling type Rule105846932.
- Thompson_sampling type YagoPermanentlyLocatedEntity.
- Thompson_sampling comment "In artificial intelligence, Thompson sampling, named after William R. Thompson, is a heuristic for choosing actions that addresses the exploration-exploitation dilemma in the multi-armed bandit problem. It consists in choosing the action that maximizes the expected reward with respect to a randomly drawn belief.".
- Thompson_sampling label "Thompson sampling".
- Thompson_sampling sameAs m.0hr0s1t.
- Thompson_sampling sameAs Q7795822.
- Thompson_sampling sameAs Q7795822.
- Thompson_sampling sameAs Thompson_sampling.
- Thompson_sampling wasDerivedFrom Thompson_sampling?oldid=584877611.
- Thompson_sampling isPrimaryTopicOf Thompson_sampling.