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:
“There is nothing man will not attempt when great enterprises hold out the promise of great rewards.”
—Titus Livius (Livy)
“And just as there are no words for the surface, that is,
No words to say what it really is, that it is not
Superficial but a visible core, then there is
No way out of the problem of pathos vs. experience.”
—John Ashbery (b. 1927)