Penguins Can Make Cake

Until quite recently, it was taken for granted in AI-and cognitive science more broadlythat activity resulted from the creation and execution of plans. In 1985, several researchers, including myself, independently realized that plans and planning are not necessary-or necessarily useful-in activity. Since this time, a number of alternatives have been proposed. In this issue of AI Magazine, Matthew Ginsberg, in “Universal Planning: An (Almost) Universally Bad Idea,” analyzes one such alternative, Marcel Schoppers’s universal plans. He also extends this analysis to a number of other systems, including Pengi (A~gre and Chapman 1987), which was designed by Phil Agre and myself. Ginsberg’s criticisms of universal plans rest on computational complexity arguments. Using universal plans, he says, is infeasible because their size is exponential in the number of possible domain states. Representing such a plan is infeasible in even quite small realistic domains. I’m sympathetic to such arguments, having made similar ones to The Counting Argument