▁( non - prob abil istic ) ▁uncertainty , ▁these ▁prob abilities ▁represent ▁the ▁decision ▁mak er ' s ▁" deg ree ▁of ▁belief " ▁in ▁a ▁specific ▁real ization . ▁ ▁In ▁our ▁example , ▁suppose ▁there ▁are ▁only ▁five ▁possible ▁realiz ations ▁of ▁the ▁uncertain ▁re venue ▁to ▁allocation ▁function . ▁The ▁decision ▁mak er ▁bel ieves ▁that ▁the ▁estimated ▁function ▁is ▁the ▁most ▁likely , ▁and ▁that ▁the ▁lik elihood ▁decre ases ▁as ▁the ▁difference ▁from ▁the ▁estimate ▁increases . ▁Figure ▁ 1 1 ▁exempl ifies ▁such ▁a ▁probability ▁distribution . ▁ ▁Now , ▁for ▁any ▁allocation , ▁one ▁can ▁construct ▁a ▁probability ▁distribution ▁of ▁the ▁re venue , ▁based ▁on ▁his ▁prior ▁belief s . ▁The ▁decision ▁mak er ▁can ▁then ▁choose ▁the ▁allocation ▁with ▁the ▁highest ▁expected ▁re venue , ▁with ▁the ▁lowest ▁probability ▁for ▁an ▁un accept able ▁re venue , ▁etc . ▁ ▁The ▁most ▁problem atic ▁step ▁of ▁this ▁analysis ▁is ▁the ▁choice ▁of ▁the ▁realiz ations ▁prob abilities . ▁When ▁there ▁is ▁an ▁extensive ▁and ▁relevant ▁past ▁experience , ▁an ▁expert ▁may ▁use ▁this ▁experience ▁to ▁construct ▁a ▁probability ▁distribution . ▁But ▁even ▁with ▁extensive ▁past ▁experience , ▁when ▁some ▁parameters ▁change , ▁the ▁expert ▁may ▁only ▁be ▁able ▁to ▁estimate ▁that ▁ ▁is ▁more ▁likely ▁than ▁, ▁but ▁will ▁not ▁be ▁able ▁to ▁reli ably ▁quant ify ▁this ▁difference . ▁Furthermore , ▁when ▁conditions ▁change ▁dr ast ically , ▁or ▁when ▁there ▁is ▁no ▁past ▁experience ▁at ▁all , ▁it ▁may ▁prove ▁to