be ▁tant amount ▁to ▁eng aging ▁in ▁wish ful ▁thinking . ▁▁ ▁In ▁short , ▁the ▁situations ▁that ▁info - g ap ▁is ▁designed ▁to ▁take ▁on ▁are ▁demand ing ▁in ▁the ▁extreme . ▁ ▁Hence , ▁the ▁challenge ▁that ▁one ▁faces ▁concept ually , ▁method olog ically ▁and ▁techn ically ▁is ▁considerable . ▁The or ists ▁can ▁examine ▁whether ▁info - g ap ▁robust ness ▁analysis ▁succeed s ▁in ▁this ▁task , ▁and ▁whether ▁the ▁tools ▁that ▁it ▁dep lo ys ▁in ▁this ▁effort ▁are ▁different ▁from ▁those ▁made ▁available ▁by ▁Wald ' s ▁( 1 9 4 5 ) ▁Max imin ▁parad ig m ▁especially ▁for ▁robust ▁optimization . ▁ ▁Wald ' s ▁Max imin ▁parad ig m ▁▁ ▁The ▁basic ▁idea ▁behind ▁this ▁famous ▁parad ig m ▁can ▁be ▁expressed ▁in ▁plain ▁language ▁as ▁follows : ▁Max imin ▁Rule ▁The ▁maxim in ▁rule ▁tells ▁us ▁to ▁rank ▁alternatives ▁by ▁their ▁worst ▁possible ▁out comes : ▁we ▁are ▁to ▁adopt ▁the ▁alternative ▁the ▁worst ▁outcome ▁of ▁which ▁is ▁superior ▁to ▁the ▁worst ▁outcome ▁of ▁the ▁others . Raw ls ▁( 1 9 7 1 , ▁p .   1 5 2 ) ▁ ▁Thus , ▁ ▁according ▁to ▁this ▁parad ig m , ▁ ▁in ▁the ▁framework ▁of ▁decision - making ▁under ▁severe ▁uncertainty , ▁the ▁robust ness ▁of ▁an ▁alternative ▁is ▁a ▁measure ▁of ▁how ▁well ▁this ▁alternative ▁can ▁co pe ▁with ▁the ▁worst ▁uncertain ▁outcome ▁that ▁it ▁can ▁generate . ▁Need less ▁to ▁say , ▁this ▁attitude ▁towards ▁severe