In computational complexity theory, a promise problem is a generalization of a decision problem where the input is promised to belong to a subset of all possible inputs. Unlike decision problems, the yes instances (the inputs for which an algorithm must return yes) and no instances do not exhaust the set of all inputs. Intuitively, the algorithm has been promised that the input does indeed belong to set of yes instances or no instances. There may be inputs which are neither yes or no. If such an input is given to an algorithm for solving a promise problem, the algorithm is allowed to output anything.
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Famous quotes containing the words promise and/or problem:
“We grew up founding our dreams on the infinite promise of American advertising. I still believe that one can learn to play the piano by mail and that mud will give you a perfect complexion.”
—Zelda Fitzgerald (1900–1948)
“The family environment in which your children are growing up is different from that in which you grew up. The decisions our parents made and the strategies they used were developed in a different context from what we face today, even if the “content” of the problem is the same. It is a mistake to think that our own experience as children and adolescents will give us all we need to help our children. The rules of the game have changed.”
—Lawrence Kutner (20th century)