probability theory and machine learning, the multi-armed bandit problem (sometimes called the K- or N-armed bandit problem) is a problem in which a decision...

problems concerning the scheduling of a batch of stochastic jobs, multi-armed bandit problems, and problems concerning the scheduling of queueing systems...

actions that address the exploration-exploitation dilemma in the multi-armed bandit problem. It consists of choosing the action that maximizes the expected...

expected reward." He then moves on to the "Multi–armed bandit problem" where each pull on a "one armed bandit" lever is allocated a reward function for...

up bandit in Wiktionary, the free dictionary. A bandit is a person who engages in banditry. Bandit, The Bandit or Bandits may also refer to: A Bandit, a...

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include developing minimax rate for multi-armed bandits, linear bandits, developing an optimal algorithm for bandit convex optimization, and solving long-standing...

noted for his work in Markov decision process, Gittins index, the multi-armed bandit, Markov chains and other related fields. Katehakis was born and grew...

make good use of resources of all types. An example of this is the multi-armed bandit problem. Exploratory analysis of Bayesian models is an adaptation...

a unique white blood cell Multi-armed bandit, a problem in probability theory Queen Mab, a fairy in English literature Multi-author blog Yutanduchi Mixteco...