▁uncertainty . ▁ ▁The ▁opportun eness ▁function ▁in ▁eq .   ( 2 ) ▁involves ▁a ▁minim ization , ▁however ▁not , ▁as ▁might ▁be ▁expected , ▁of ▁the ▁damage ▁which ▁can ▁acc r ue ▁from ▁unknown ▁ad verse ▁events . ▁The ▁least ▁horizon ▁of ▁uncertainty ▁is ▁sought ▁at ▁which ▁decision ▁ ▁enables ▁( but ▁does ▁not ▁necessarily ▁guarantee ) ▁large ▁wind fall ▁gain . ▁Un like ▁the ▁robust ness ▁function , ▁the ▁opportun eness ▁function ▁does ▁not ▁satisf ice , ▁it ▁" wind falls ". ▁Wind fall ing ▁prefer ences ▁are ▁those ▁which ▁prefer ▁actions ▁for ▁which ▁the ▁opportun eness ▁function ▁takes ▁a ▁small ▁value . ▁When ▁ ▁is ▁used ▁to ▁choose ▁an ▁action ▁, ▁one ▁is ▁" wind fall ing " ▁by ▁optim izing ▁the ▁opportun eness ▁from ▁prop it ious ▁uncertainty ▁in ▁an ▁attempt ▁to ▁enable ▁highly ▁am bit ious ▁goals ▁or ▁re wards . ▁ ▁Given ▁a ▁scalar ▁reward ▁function ▁, ▁depending ▁on ▁the ▁decision ▁vector ▁ ▁and ▁the ▁info - g ap - unc ertain ▁function ▁, ▁the ▁minimal ▁requirement ▁in ▁eq .   ( 1 ) ▁is ▁that ▁the ▁reward ▁ ▁be ▁no ▁less ▁than ▁a ▁critical ▁value ▁. ▁Like wise , ▁the ▁swe eping ▁success ▁in ▁eq . ▁( 2 ) ▁is ▁att ain ment ▁of ▁a ▁" w ild est ▁dream " ▁level ▁of ▁reward ▁ ▁which ▁is ▁much ▁greater ▁than ▁. ▁Usually ▁neither ▁of ▁these ▁threshold ▁values , ▁ ▁and ▁, ▁is ▁chosen ▁ir rev oc ably ▁before ▁performing ▁the ▁decision ▁analysis . ▁R