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Cumulative Space in Black-White Pebbling and Resolution
KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.
KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.ORCID iD: 0000-0002-2700-4285
KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.ORCID iD: 0000-0002-1487-445X
2017 (English)Conference paper (Refereed)
Place, publisher, year, edition, pages
2017.
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-206582OAI: oai:DiVA.org:kth-206582DiVA: diva2:1093402
Conference
8th Innovations in Theoretical Computer Science (ITCS) conference, Berkeley, January 9-11, 2017
Note

QC 20170509

Available from: 2017-05-05 Created: 2017-05-05 Last updated: 2017-05-09Bibliographically approved
In thesis
1. Space in Proof Complexity
Open this publication in new window or tab >>Space in Proof Complexity
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

ropositional proof complexity is the study of the resources that are needed to prove formulas in propositional logic. In this thesis we are concerned with the size and space of proofs, and in particular with the latter.

Different approaches to reasoning are captured by corresponding proof systems. The simplest and most well studied proof system is resolution, and we try to get our understanding of other proof systems closer to that of resolution.

In resolution we can prove a space lower bound just by showing that any proof must have a large clause. We prove a similar relation between resolution width and polynomial calculus space that lets us derive space lower bounds, and we use it to separate degree and space.

For cutting planes we show length-space trade-offs. This is, there are formulas that have a proof in small space and a proof in small length, but there is no proof that can optimize both measures at the same time.

We introduce a new measure of space, cumulative space, that accounts for the space used throughout a proof rather than only its maximum. This is exploratory work, but we can also prove new results for the usual space measure.

We define a new proof system that aims to capture the power of current SAT solvers, and we show a landscape of length-space trade-offs comparable to those in resolution.

To prove these results we build and use tools from other areas of computational complexity. One area is pebble games, very simple computational models that are useful for modelling space. In addition to results with applications to proof complexity, we show that pebble game cost is PSPACE-hard to approximate.

Another area is communication complexity, the study of the amount of communication that is needed to solve a problem when its description is shared by multiple parties. We prove a simulation theorem that relates the query complexity of a function with the communication complexity of a composed function.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2017. 318 p.
Series
TRITA-CSC-A, ISSN 1653-5723 ; 2017:15
Keyword
proof complexity, resolution, polynomial calculus, cutting planes, space complexity, computational complexity, pebble games, communication complexity, CDCL
National Category
Computer Science
Research subject
Computer Science
Identifiers
urn:nbn:se:kth:diva-206571 (URN)978-91-7729-422-1 (ISBN)
Public defence
2017-06-09, E2, Lindstedtsvägen, 3, Stockholm, 14:00 (English)
Opponent
Supervisors
Funder
EU, FP7, Seventh Framework Programme, 279611
Note

QC 20170509

Available from: 2017-05-10 Created: 2017-05-09 Last updated: 2017-05-10Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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Output format
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