rob ust ness ) ▁| ▁( 1 a ) ▁| - ▁| ▁| ▁( o pport un eness ) ▁| ▁( 2 a ) ▁| } ▁Form ally , ▁{ | ▁width =" 1 0 0 %" ▁border =" 0 " ▁| ▁| ▁( rob ust ness ) ▁| ▁( 1 b ) ▁| - ▁| ▁| ▁( o pport un eness ) ▁| ▁( 2 b ) ▁| } ▁ ▁We ▁can ▁" read " ▁eq .   ( 1 ) ▁as ▁follows . ▁The ▁robust ness ▁ ▁of ▁decision ▁vector ▁ ▁is ▁the ▁greatest ▁value ▁of ▁the ▁horizon ▁of ▁uncertainty ▁ ▁for ▁which ▁specified ▁minimal ▁requirements ▁are ▁always ▁satisfied . ▁ ▁express es ▁robust ness ▁— ▁the ▁degree ▁of ▁resistance ▁to ▁uncertainty ▁and ▁imm unity ▁against ▁failure ▁— ▁so ▁a ▁large ▁value ▁of ▁ ▁is ▁des irable . ▁Rob ust ness ▁is ▁defined ▁as ▁a ▁worst - case ▁scenario ▁up ▁to ▁the ▁horizon ▁of ▁uncertainty : ▁how ▁large ▁can ▁the ▁horizon ▁of ▁uncertainty ▁be ▁and ▁still , ▁even ▁in ▁the ▁worst ▁case , ▁achieve ▁the ▁critical ▁level ▁of ▁outcome ? ▁ ▁Eq .   ( 2 ) ▁states ▁that ▁the ▁opportun eness ▁ ▁is ▁the ▁least ▁level ▁of ▁uncertainty ▁ ▁which ▁must ▁be ▁toler ated ▁in ▁order ▁to ▁enable ▁the ▁possibility ▁of ▁swe eping ▁success ▁as ▁a ▁result ▁of ▁dec isions ▁. ▁ ▁is ▁the ▁imm unity ▁against ▁wind fall ▁reward , ▁so ▁a ▁small ▁value ▁of ▁ ▁is ▁des irable . ▁A ▁small ▁value ▁of ▁ ▁reflect s ▁the ▁opport