▁function ▁sens ibly ▁when ▁there ▁are ▁' se vere ' ▁knowledge ▁g aps ." ▁The ▁info - g ap ▁robust ness ▁and ▁opportun eness ▁functions ▁provide ▁" a ▁formal ▁framework ▁to ▁explore ▁the ▁kinds ▁of ▁spec ulations ▁that ▁occur ▁intuit ively ▁when ▁exam ining ▁decision ▁options ." ▁ ▁Burg man ▁then ▁proceed s ▁to ▁develop ▁an ▁info - g ap ▁robust - s atisf icing ▁strategy ▁for ▁protect ing ▁the ▁end anger ed ▁orange - bel lied ▁par rot . ▁Similarly , ▁Vin ot , ▁C og an ▁and ▁C ip ol la ▁ ▁discuss ▁engineering ▁design ▁and ▁note ▁that ▁" the ▁down side ▁of ▁a ▁model - based ▁analysis ▁lies ▁in ▁the ▁knowledge ▁that ▁the ▁model ▁behavior ▁is ▁only ▁an ▁approximation ▁to ▁the ▁real ▁system ▁behavior . ▁Hence ▁the ▁question ▁of ▁the ▁honest ▁designer : ▁how ▁sensitive ▁is ▁my ▁measure ▁of ▁design ▁success ▁to ▁un cert aint ies ▁in ▁my ▁system ▁representation ? ▁... ▁It ▁is ▁evident ▁that ▁if ▁model - based ▁analysis ▁is ▁to ▁be ▁used ▁with ▁any ▁level ▁of ▁confidence ▁then ▁... ▁[ one ▁must ] ▁attempt ▁to ▁satisfy ▁an ▁acceptable ▁sub - opt imal ▁level ▁of ▁performance ▁while ▁remaining ▁maxim ally ▁robust ▁to ▁the ▁system ▁un cert aint ies ." ▁They ▁proceed ▁to ▁develop ▁an ▁info - g ap ▁robust - s atisf icing ▁design ▁procedure ▁for ▁an ▁a eros pace ▁application . ▁ ▁Altern atives ▁Of ▁course , ▁decision ▁in ▁the ▁face ▁of ▁uncertainty ▁is ▁nothing ▁new , ▁and ▁attempts ▁to ▁deal ▁with ▁it ▁have ▁a ▁long ▁history