▁Disc uss ion ▁ ▁Sat isf icing ▁and ▁bounded ▁rational ity ▁ ▁It ▁is ▁correct ▁that ▁the ▁info - g ap ▁robust ness ▁function ▁is ▁local , ▁and ▁has ▁restricted ▁quant itative ▁value ▁in ▁some ▁cases . ▁However , ▁a ▁major ▁purpose ▁of ▁decision ▁analysis ▁is ▁to ▁provide ▁focus ▁for ▁subject ive ▁jud g ments . ▁That ▁is , ▁regardless ▁of ▁the ▁formal ▁analysis , ▁a ▁framework ▁for ▁discussion ▁is ▁provided . ▁Without ▁entering ▁into ▁any ▁particular ▁framework , ▁or ▁characteristics ▁of ▁frameworks ▁in ▁general , ▁discussion ▁follows ▁about ▁propos als ▁for ▁such ▁frameworks . ▁ ▁Simon ▁▁ ▁introduced ▁the ▁idea ▁of ▁bounded ▁rational ity . ▁Lim itations ▁on ▁knowledge , ▁understanding , ▁and ▁computational ▁cap ability ▁const rain ▁the ▁ability ▁of ▁decision ▁mak ers ▁to ▁identify ▁optimal ▁choices . ▁Simon ▁advoc ated ▁satisf icing ▁rather ▁than ▁optim izing : ▁seeking ▁ade qu ate ▁( r ather ▁than ▁optimal ) ▁out comes ▁given ▁available ▁resources . ▁Schw art z , ▁Con l isk ▁ ▁and ▁others ▁discuss ▁extensive ▁evidence ▁for ▁the ▁phenomen on ▁of ▁bounded ▁rational ity ▁among ▁human ▁decision ▁mak ers , ▁as ▁well ▁as ▁for ▁the ▁advantages ▁of ▁satisf icing ▁when ▁knowledge ▁and ▁understanding ▁are ▁def ic ient . ▁The ▁info - g ap ▁robust ness ▁function ▁provides ▁a ▁means ▁of ▁implementing ▁a ▁satisf icing ▁strategy ▁under ▁bounded ▁rational ity . ▁For ▁instance , ▁in ▁discuss ing ▁bounded ▁rational ity ▁and ▁satisf icing ▁in ▁conservation ▁and ▁environmental ▁management , ▁Burg man ▁notes ▁that ▁" Info - g ap ▁theory ▁... ▁can