Adaptive logspace and depth-bounded reducibilities

Author

Balcázar, José L.

Author_Institution

Dept. of de Llenguatges i Sistemes Inf., Univ. Politecnica de Catalunya, Barcelona, Spain

fYear

1991

fDate

30 Jun-3 Jul 1991

Firstpage

240

Lastpage

254

Abstract

The author discusses a number of results regarding the study of the computational power of depth-bounded reducibilities, their use to classify the complexity of computational problems, and their characterizations in terms of other computational models. In particular, problems arising in the design of concurrent systems are studied, and two kinds of logarithmic space reductions are defined. The first one is nonadaptive and equivalent in many respects to the oracle set model. The second provides a notion of adaptive logspace reducibility which turns out to characterize precisely depth-bounded reductions. The closures of NP under these reducibilities are also treated

Keywords

computational complexity; NP closures; adaptive logspace reducibility; computational complexity; computational models; computational power; concurrent systems; depth-bounded reducibilities; logarithmic space reductions; oracle set model; Algorithms; Circuits; Computational modeling; Concurrent computing; Power system modeling; Robustness; Stacking; Turing machines; Yarn;

fLanguage

English

Publisher

ieee

Conference_Titel

Structure in Complexity Theory Conference, 1991., Proceedings of the Sixth Annual

Conference_Location

Chicago, IL

Print_ISBN

0-8186-2255-5

Type

conf

DOI

10.1109/SCT.1991.160267

Filename

160267