verse ▁or ▁favor able . ▁Ad vers ity ▁ent ails ▁the ▁possibility ▁of ▁failure , ▁while ▁favor ability ▁is ▁the ▁opportunity ▁for ▁swe eping ▁success . ▁Info - g ap ▁decision ▁theory ▁is ▁based ▁on ▁quant ifying ▁these ▁two ▁aspects ▁of ▁uncertainty , ▁and ▁choosing ▁an ▁action ▁which ▁addresses ▁one ▁or ▁the ▁other ▁or ▁both ▁of ▁them ▁simultaneously . ▁The ▁per n icious ▁and ▁prop it ious ▁aspects ▁of ▁uncertainty ▁are ▁quant ified ▁by ▁two ▁" imm unity ▁functions ": ▁the ▁robust ness ▁function ▁express es ▁the ▁imm unity ▁to ▁failure , ▁while ▁the ▁opportun eness ▁function ▁express es ▁the ▁imm unity ▁to ▁wind fall ▁gain . ▁ ▁Rob ust ness ▁and ▁opportun eness ▁functions ▁ ▁The ▁robust ness ▁function ▁express es ▁the ▁greatest ▁level ▁of ▁uncertainty ▁at ▁which ▁failure ▁cannot ▁occur ; ▁the ▁opportun eness ▁function ▁is ▁the ▁least ▁level ▁of ▁uncertainty ▁which ▁ent ails ▁the ▁possibility ▁of ▁swe eping ▁success . ▁The ▁robust ness ▁and ▁opportun eness ▁functions ▁address , ▁respectively , ▁the ▁per n icious ▁and ▁prop it ious ▁fac ets ▁of ▁uncertainty . ▁ ▁Let ▁ ▁be ▁a ▁decision ▁vector ▁of ▁parameters ▁such ▁as ▁design ▁variables , ▁time ▁of ▁init iation , ▁model ▁parameters ▁or ▁oper ational ▁options . ▁We ▁can ▁verb ally ▁express ▁the ▁robust ness ▁and ▁opportun eness ▁functions ▁as ▁the ▁maximum ▁or ▁minimum ▁of ▁a ▁set ▁of ▁values ▁of ▁the ▁uncertainty ▁parameter ▁ ▁of ▁an ▁info - g ap ▁model : ▁{ | ▁width =" 1 0 0 %" ▁border =" 0 " ▁| ▁| ▁(