Average case optimality

AbstractInformation-based complexity studies problems where only partial and contaminated information is available. One simply states how well a problem should be solved and indicates the type of information available. The theory then yields the optimal information, the optimal algorithm, and bounds on the problem complexity. In this paper we discuss some recent results dealing with the average case setting, i.e., the setting where both the cost and the error are measured on the average