A bandit problem consisting of a sequence of n choices ( n →∞) from a number of infinitely many Bernoulli arms is considered. The parameters of Bernoulli arms are independent and identically distributed random
We formulate GAI as a pure-exploration problem in the fixed confidence setting, which is often considered in conventional pure-exploration problems. In the fixed confidence setting, an acceptance error rate δ is fixed in advance, and we minimize the number of pulling arms needed to assure the ...
Applicationsto stochastic schedulings,equentialclinicaltrialsand a class of searchproblemsare discussed. Keywords:BANDITPROCESSES;DYNAMICALLOCATIONINDICES; TWO-ARMEDBANDITPROBLEM; MARKOVDECISIONPROCESSESO; PTIMALRESOURCEALLOCATIONS; EQUENTIALRANDOM SAMPLING;CHEMICALRESEARCH;CLINICALTRIALS;SEARCH A schedulinpgroblem ...
(arms). We introduce the classical theory for multi-armed bandit processes in Section 6.1, and consider open bandit processes in which infinitely many arms are allowed in Section 6.2. An extension to generalized open bandit processes is given in Section 6.3. Finally, a concise account for ...
A note on infinite-armed Bernoulli bandit problems with generalized beta prior distributionsdoi:10.1007/BF02762039Dynamic allocation of Bernoulli processesk-failure strategym-run strategyN-learning strategynon-recallingm-run strategysequential experimentationA bandit problem with infinitely many Bernoulli arms ...