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Acceptor-definable counting classes

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dc.contributor.author Kiayias, A en
dc.contributor.author Pagourtzis, A en
dc.contributor.author Sharma, K en
dc.contributor.author Zachos, S en
dc.date.accessioned 2014-03-01T01:18:35Z
dc.date.available 2014-03-01T01:18:35Z
dc.date.issued 2003 en
dc.identifier.issn 0302-9743 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/15099
dc.relation.uri http://www.scopus.com/inward/record.url?eid=2-s2.0-35248812634&partnerID=40&md5=82cc8cbdb0ab8b9077a103c5ffedc38a en
dc.subject.classification Computer Science, Theory & Methods en
dc.subject.other COMPLEXITY en
dc.title Acceptor-definable counting classes en
heal.type journalArticle en
heal.language English en
heal.publicationDate 2003 en
heal.abstract Counting functions that can be defined on non-deterministic acceptors (Turing machines without output), as opposed to those defined by transducers (Turing machines with output), have attracted much interest since 1979, when Valiant introduced the important class #P [19]. Apart from #P, several such classes have been defined in the literature [2, 5, 3, 12, 6]. Here we study the path-order complexity classes RAP, LAP and MAP, introduced in [6], which consist of functions that output the order of the rightmost, leftmost and middle accepting computation path (respectively) of a polynomial-time non-deterministic Turing acceptor (PNTM). We also consider TotP [6], the class of functions that output the total number of paths of a PNTM. We show several properties of these classes. In particular we prove that RAP and LAP are are equivalent under the Cook[1] sense with #P and TotP. This implies that all these classes are equally powerful when used as oracles to a polynomial computation, even if only one query is allowed. We also show that problems #PERFECT MATCHINGS and #DNF-SAT are complete for RAP and LAP in the Cook[1] sense and for MAP in the Cook sense. Path-order classes give rise to corresponding path-order operators; these operators applied on the class NP provide alternative characterizations for known classes of optimization problems. Using these characterizations, we present natural complete problems for optimization classes. © Springer-Verlag Berlin Heidelberg 2003. en
heal.publisher SPRINGER-VERLAG BERLIN en
heal.journalName Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) en
heal.bookName LECTURE NOTES IN COMPUTER SCIENCE en
dc.identifier.isi ISI:000183490000029 en
dc.identifier.volume 2563 en
dc.identifier.spage 453 en
dc.identifier.epage 463 en


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