Turing machines with sublogarithmic space / edited by Andrzej Szepietowski.
Contributor(s): Szepietowski, AndrzejMaterial type: TextSeries: SerienbezeichnungLecture notes in computer science: 843.Publisher: Berlin ; New York : Springer-Verlag, ©1994Description: 1 online resource (viii, 114 pages)Content type: text Media type: computer Carrier type: online resourceISBN: 9783540486695; 3540486690Subject(s): Turing machines | Computational complexity | Computational complexity | Turing machines | Algebra | Mathematics | Physical Sciences & MathematicsGenre/Form: Online resources. | Electronic books. Additional physical formats: Print version:: No titleDDC classification: 511.3 LOC classification: QA267 | .T8 1994Online resources: Click here to access online
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Includes bibliographical references (pages 111-112) and indexes.
This comprehensive monograph investigates the computational power of Turing machines with sublogarithmic space. The studies are devoted to the Turing machine model introduced by Stearns, Hartmanis, and Lewis (1965) with a two-way read-only input tape and a separate two-way read-write work tape. The book presents the key results on space complexity, also as regards the classes of languages acceptable, under the perspective of a sublogarithmic number of cells used during computation. It originates from courses given by the author at the Technical University of Gdansk and Gdansk University in 1991 and 1992. It was finalized in 1994 when the author visited Paderborn University and includes the most recent contributions to the field.
Basic Notions -- Languages acceptable with logarithmic space -- Examples of languages acceptable with sublogarithmic space -- Lower bounds for accepting non-regular languages -- Space constructible functions -- Halting property and closure under complement -- Strong versus weak mode of space complexity -- Padding -- Deterministic versus nondeterministic Turing machines -- Space hierarchy -- Closure under concatenation -- Alternating hierarchy -- Independent complement -- Other models of Turing machines.