Mikoláš Janota

Dr. Mikoláš Janota

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Research Focus & Metrics

Academic Career Length

20Years (2007-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 May 2016 in Artificial Intelligence
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Journal Article
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MJMikoláš Janota
Mikoláš Janota
WKWilliam Klieber
William Klieber
JMJoao Marques-Silva
Joao Marques-Silva
ECEdmund Clarke
Edmund Clarke

1 April 2015 in Theoretical Computer Science
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Journal Article
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MJMikoláš Janota
Mikoláš Janota
JMJoao Marques-Silva
Joao Marques-Silva

1 January 2012
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Book Chapter
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PDF file
MJMikoláš Janota
Mikoláš Janota
WKWilliam Klieber
William Klieber
JMJoao Marques-Silva
Joao Marques-Silva
ECEdmund Clarke
Edmund Clarke

1 January 2015 in AI Communications
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Journal Article
Closed access
PDF file
MJMikoláš Janota
Mikoláš Janota
ILInês Lynce
Inês Lynce
JMJoao Marques-Silva
Joao Marques-Silva
The problem of propositional satisfiability (SAT) has found a number of applications in both theoretical and practical computer science. In many applications, however, knowing a formula's satisfiability alone is insufficient. Often, some other proper

1 January 2013
Verified
Book Chapter
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JMJoao Marques-Silva
Joao Marques-Silva
MJMikoláš Janota
Mikoláš Janota
ABAnton Belov
Anton Belov

12 September 2019 in ACM Transactions on Computation Theory
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Journal Article
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OBOlaf Beyersdorff
Olaf Beyersdorff
LCLeroy Chew
Leroy Chew
MJMikoláš Janota
Mikoláš Janota
Modern QBF solvers typically use two different paradigms, conflict-driven clause learning (CDCL) solving or expansion solving. Proof systems for quantified Boolean formulas (QBFs) provide a theoretical underpinning for the performance of these solvers, with Q-Resolution and its extensions relating to CDCL solving and ∀Exp+Res relating to expansion solving. This article defines two novel calculi, which are resolution-based and enable unification of some of the principal existing resolution-based QBF calculi, namely Q-resolution, long-distance Q-resolution and the expansion-based calculus ∀Exp+Res. However, the proof complexity of the QBF resolution proof systems is currently not well understood. In this article, we completely determine the relative power of the main QBF resolution systems, settling in particular the relationship between the two different types of resolution-based QBF calculi: proof systems for CDCL-based solvers (Q-resolution, universal, and long-distance Q-resolution) and proof systems for expansion-based solvers (∀Exp+Res and its generalizations IR-calc and IRM-calc defined here). The most challenging part of this comparison is to exhibit hard formulas that underlie the exponential separations of the aforementioned proof systems. To this end, we exhibit a new and elegant proof technique for showing lower bounds in QBF proof systems based on strategy extraction. This technique provides a direct transfer of circuit lower bounds to lengths-of-proofs lower bounds. We use our method to show the hardness of a natural class of parity formulas for Q-resolution and universal Q-resolution. Variants of the formulas are hard for even stronger systems such as long-distance Q-resolution and extensions. With a completely different and novel counting argument, we show the hardness of the prominent formulas of Kleine Büning et al. [51] for the strong expansion-based calculus IR-calc.