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We develop an index policy for finite-horizon Bernoulli multi-armed bandits from minimax solutions to single-arm bandit (SAB) problems. Each SAB problem involves choosing between an unknown Bernoulli arm and a known reward. We show that minimizing worst-case regret of SAB problems over all non-anticipative policies adm...
A shrinkage path heuristic is proposed that reduces the solution of a DRO problem to a one-dimensional search over the line segment connecting the sample average approximation (SAA) and the (more demanding but practically solvable) classical robust optimization solution.
A new mathematical programming perspective on FMDPs is introduced that swaps hand-crafted machinery for off-the-shelf optimization solvers, unifies and extends existing treatments of context-specific independence, and pairs an approximate linear program with a novel cutting-plane algorithm.
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