We study a bad arm existing checking problem in which a player's task is to
judge whether a positive arm exists or not among given K arms by drawing as
small number of arms as possible. Here, an arm is positive if its expected loss
suffered by drawing the arm is at least a given threshold. This problem is a
formalization of diagnosis of disease or machine failure. An interesting
structure of this problem is the asymmetry of positive and negative
(non-positive) arms' roles; finding one positive arm is enough to judge
existence while all the arms must be discriminated as negative to judge
non-existence. We propose an algorithms with arm selection policy (policy to
determine the next arm to draw) and stopping condition (condition to stop
drawing arms) utilizing this asymmetric problem structure and prove its
effectiveness theoretically and empirically.