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  2. Complexity class - Wikipedia

    en.wikipedia.org/wiki/Complexity_class

    A problem is hard for a class of problems C if every problem in C can be polynomial-time reduced to . Thus no problem in C is harder than , since an algorithm for allows us to solve any problem in C with at most polynomial slowdown. Of particular importance, the set of problems that are hard for NP is called the set of NP-hard problems.

  3. List of complexity classes - Wikipedia

    en.wikipedia.org/wiki/List_of_complexity_classes

    The hardest problems in PSPACE. PTAS: Polynomial-time approximation scheme (a subclass of APX). QIP: Solvable in polynomial time by a quantum interactive proof system. QMA: Quantum analog of NP. R: Solvable in a finite amount of time. RE: Problems to which we can answer "YES" in a finite amount of time, but a "NO" answer might never come. RL

  4. Computational hardness assumption - Wikipedia

    en.wikipedia.org/wiki/Computational_hardness...

    Many worst-case computational problems are known to be hard or even complete for some complexity class, in particular NP-hard (but often also PSPACE-hard, PPAD-hard, etc.). This means that they are at least as hard as any problem in the class C {\displaystyle C} .

  5. Diffie–Hellman problem - Wikipedia

    en.wikipedia.org/wiki/Diffie–Hellman_problem

    In fact, significant progress (by den Boer, Maurer, Wolf, Boneh and Lipton) has been made towards showing that over many groups the DHP is almost as hard as the DLP. There is no proof to date that either the DHP or the DLP is a hard problem, except in generic groups (by Nechaev and Shoup). A proof that either problem is hard implies that P ≠ NP.

  6. Computational complexity theory - Wikipedia

    en.wikipedia.org/wiki/Computational_complexity...

    The notion of hard problems depends on the type of reduction being used. For complexity classes larger than P, polynomial-time reductions are commonly used. In particular, the set of problems that are hard for NP is the set of NP-hard problems. If a problem is in and hard for , then is said to be complete for .

  7. Artificial general intelligence - Wikipedia

    en.wikipedia.org/wiki/Artificial_general...

    A problem is informally called "AI-complete" or "AI-hard" if it is believed that in order to solve it, one would need to implement AGI, because the solution is beyond the capabilities of a purpose-specific algorithm. [44] There are many problems that have been conjectured to require general intelligence to solve as well as humans.

  8. Musk's X ineffective against surge in US election ... - AOL

    www.aol.com/news/musks-x-ineffective-against...

    Of the 283 misleading X posts that CCDH analyzed, 209, or 74% of the posts, did not show accurate notes to all X users correcting false and misleading claims about the elections, the report said.

  9. Hamiltonian path problem - Wikipedia

    en.wikipedia.org/wiki/Hamiltonian_path_problem

    The problems of finding a Hamiltonian path and a Hamiltonian cycle can be related as follows: In one direction, the Hamiltonian path problem for graph G can be related to the Hamiltonian cycle problem in a graph H obtained from G by adding a new universal vertex x, connecting x to all vertices of G. Thus, finding a Hamiltonian path cannot be ...