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Co-NP-complete : ウィキペディア英語版 | Co-NP-complete
In complexity theory, computational problems that are co-NP-complete are those that are the hardest problems in co-NP, in the sense that any problem in co-NP can be reformulated as a special case of any co-NP complete problem with only polynomial overhead. If P is different from co-NP, then all of the co-NP complete problems are not solvable in polynomial time. If there exists a way to solve a co-NP-complete problem quickly, then that algorithm can be used to solve all co-NP problems quickly. Each Co-NP-complete problem is the complement of an NP-complete problem. There are some problems in both NP and co-NP, for example all problems in P or integer factorization; however, it is not known if the sets are equal, although inequality is thought more likely. See co-NP and NP-complete for more details. Fortune showed in 1979 that if any sparse language is co-NP-complete (or even just co-NP-hard), then ,〔S. Fortune. A note on sparse complete sets. ''SIAM Journal on Computing'', volume 8, issue 3, pp.431–433. 1979.〕 a critical foundation for Mahaney's theorem. ==Formal definition== A decision problem ''C'' is co-NP-complete if it is in co-NP and if every problem in co-NP is polynomial-time many-one reducible to it. This means that for every Co-NP problem ''L'', there exists a polynomial time algorithm which can transform any instance of ''L'' into an instance of ''C'' with the same truth value. As a consequence, if we had a polynomial time algorithm for ''C'', we could solve all co-NP problems in polynomial time.
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