Why is it important to know whether a problem is NP-complete?
Proving a problem NP-Complete is a research success because it frees you from having to search for an efficient and exact solution for the general problem you are studying.
What makes NP-hard difficult?
A problem is NP-hard if an algorithm for solving it can be translated into one for solving any NP-problem (nondeterministic polynomial time) problem. NP-hard therefore means “at least as hard as any NP-problem,” although it might, in fact, be harder.
Can machine learning solve NP-hard problems?
Q: Will machine learning prove useful in solving NP Complete problems? A: The short answer is “If you’re an engineer, yes. If you’re a mathematician, no.” but there’s more to it. “Solving” a problem means something very different to a mathematician than to an engineer.
How are NP-hard problems solved?
NP-Hard problems(say X) can be solved if and only if there is a NP-Complete problem(say Y) that can be reducible into X in polynomial time. NP-Complete problems can be solved by a non-deterministic Algorithm/Turing Machine in polynomial time. To solve this problem, it do not have to be in NP .
Can neural networks solve NP problems?
Graph Neural Networks (GNN) are a promising technique for bridging differential programming and combinatorial domains. In summary, our work shows that Graph Neural Networks are powerful enough to solve \mathcal{NP}-Complete problems which combine symbolic and numeric data.
When is a problem an NP hard problem?
NP-Hard Problem need not be in NP class. A problem X is NP-Complete if there is an NP problem Y, such that Y is reducible to X in polynomial time. NP-Complete problems are as hard as NP problems. A problem is NP-Complete if it is a part of both NP and NP-Hard Problem.
Can a non deterministic Turing machine solve a NP hard problem?
A non-deterministic Turing machine can solve NP-Complete problem in polynomial time. NP-Hard problems (say X) can be solved if and only if there is a NP-Complete problem (say Y) that can be reducible into X in polynomial time.
Can a NP hard problem be solved in polynomial time?
NP-Hard problems (say X) can be solved if and only if there is a NP-Complete problem (say Y) that can be reducible into X in polynomial time. NP-Complete problems can be solved by a annon-deterministic Algorithm/Turing Machine in polynomial time.