Uniformly defining complexity classes of functions
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN: 0302-9743, Vol: 1373 LNCS, Page: 607-617
1998
- 4Citations
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Metrics Details
- Citations4
- Citation Indexes4
- CrossRef3
Conference Paper Description
We introduce a general framework for the definition of function classes. Our model, which is based on polynomial time nondeterministic Turing transducers, allows uniform characterizations of FP, FP, counting classes (#·P, #·NP, #·coNP, GapP, GapP), optimization classes (max·P, min·P, max·NP, min·NP), promise classes (NPSV, #·P, c#·P), multivalued classes (FewFP, NPMV) and many more. Each such class is defined in our model by a certain family of functions. We study a reducibility notion between such families, which leads to a necessary and sufficient criterion for relativizable inclusion between function classes. As it turns out, this criterion is easily applicable and we get as a consequence e.g. that there are oracles A, B, such that min·P ⊈ #·NP, and max·NP ⊈ c#·coNP (note that no structural consequences are known to follow from the corresponding positive inclusions). © 1998 Springer-Verlag.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=23844535290&origin=inward; http://dx.doi.org/10.1007/bfb0028595; http://link.springer.com/10.1007/BFb0028595; http://link.springer.com/content/pdf/10.1007/BFb0028595; https://dx.doi.org/10.1007/bfb0028595; https://link.springer.com/chapter/10.1007/BFb0028595
Springer Science and Business Media LLC
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