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They are some of the very few NP problems not known to be in P or to be NP-complete. The graph isomorphism problem is the computational problem of determining whether two finite graphs are isomorphic. An important unsolved problem in complexity theory is whether the graph isomorphism problem is in P, NP-complete, or NP-intermediate.
The goal of the program is to answer the most famous open problem in computer science – whether P = NP – by showing that the complexity class P is not equal to the complexity class NP. The idea behind the approach is to adopt and develop advanced tools in algebraic geometry and representation theory (i.e., geometric invariant theory ) to ...
In computational complexity theory, a natural proof is a certain kind of proof establishing that one complexity class differs from another one. While these proofs are in some sense "natural", it can be shown (assuming a widely believed conjecture on the existence of pseudorandom functions) that no such proof can possibly be used to solve the P vs. NP problem.
A problem p in NP is NP-complete if every other problem in NP can be transformed (or reduced) into p in polynomial time. [citation needed] It is not known whether every problem in NP can be quickly solved—this is called the P versus NP problem.
The complexity class NP, on the other hand, contains many problems that people would like to solve efficiently, but for which no efficient algorithm is known, such as the Boolean satisfiability problem, the Hamiltonian path problem and the vertex cover problem. Since deterministic Turing machines are special non-deterministic Turing machines ...
Let P 1 and P 2 be two problems in FNP, with associated verification algorithms A 1, A 2. A reduction P 1 and P 2 is defined as two efficiently-computable functions, f and g, such that [3] f maps inputs x to P 1 to inputs f(x) to P 2 ; g maps outputs y to P 2 to outputs g(y) to P 1 ; For all x and y: if A 2 (f(x),y) returns true, then A 1 (x, g ...