ness ▁function ▁is ▁" local " ▁to ▁the ▁region ▁around ▁, ▁where ▁ ▁is ▁likely ▁to ▁be ▁substantial ly ▁in ▁error . ▁He ▁con cludes ▁that ▁therefore ▁the ▁info - g ap ▁robust ness ▁function ▁is ▁an ▁un re li able ▁assess ment ▁of ▁imm unity ▁to ▁error . ▁ ▁In ▁the ▁framework ▁of ▁classical ▁decision ▁theory , ▁info - g ap ' s ▁robust ness ▁model ▁can ▁be ▁constru ed ▁as ▁an ▁instance ▁of ▁Wald ' s ▁Max imin ▁model ▁and ▁its ▁opportun eness ▁model ▁is ▁an ▁instance ▁of ▁the ▁classical ▁Min imin ▁model . ▁Both ▁operate ▁in ▁the ▁neighborhood ▁of ▁an ▁estimate ▁of ▁the ▁parameter ▁of ▁interest ▁whose ▁true ▁value ▁is ▁subject ▁to ▁severe ▁uncertainty ▁and ▁therefore ▁is ▁likely ▁to ▁be ▁substantial ly ▁wrong . ▁Moreover , ▁the ▁consider ations ▁brought ▁to ▁bear ▁upon ▁the ▁decision ▁process ▁itself ▁also ▁origin ate ▁in ▁the ▁local ity ▁of ▁this ▁un re li able ▁estimate , ▁and ▁so ▁may ▁or ▁may ▁not ▁be ▁reflect ive ▁of ▁the ▁entire ▁range ▁of ▁dec isions ▁and ▁un cert aint ies . ▁ ▁Background , ▁working ▁assumptions , ▁and ▁a ▁look ▁ahead ▁▁ ▁Dec ision ▁under ▁severe ▁uncertainty ▁is ▁a ▁form id able ▁task ▁and ▁the ▁development ▁of ▁method ologies ▁capable ▁of ▁handling ▁this ▁task ▁is ▁even ▁a ▁more ▁ar du ous ▁undert aking . ▁ ▁Indeed , ▁over ▁the ▁past ▁si xty ▁years ▁an ▁enorm ous ▁effort ▁has ▁gone ▁into ▁the ▁development ▁of ▁such ▁method ologies . ▁ ▁Yet , ▁for ▁all ▁the ▁knowledge ▁and ▁expert ise