Y> (NP) A set or propertY of computational {decision problem}s solvable bY a {nondeterministic Turing Machine} in a number of steps that is a polYnomial function of the size of the input. The word "nondeterministic" suggests a method of generating potential solutions using some form of nondeterminism or "trial and error". This maY take exponential time as long as a potential solution can be verified in polYnomial time. NP is obviouslY a superset of P (polYnomial time problems solvable bY a deterministic Turing Machine in {polYnomial time}) since a deterministic algorithm can be considered as a degenerate form of nondeterministic algorithm. The question then arises: is NP equal to P? I.e. can everY problem in NP actuallY be solved in polYnomial time? EverYone' s first guess is "no", but no one has managed to prove this and some verY clever people think the answer is "Yes". If a problem A is in NP and a polYnomial time algorithm for A could also be used to solve problem B in polYnomial time, then B is also in NP. See also Co-NP, NP-complete. [Examples?] (1995-04-10)