article

Generating hard satisfiability problems

Authors:

Bart Selman,

David G. Mitchell,

Hector J. LevesqueAuthors Info & Claims

Artificial Intelligence, Volume 81, Issue 1-2

Pages 17 - 29

https://doi.org/10.1016/0004-3702(95)00045-3

Published: 01 March 1996 Publication History

Abstract

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Fleming NPankratov DPitassi TRobere R(2022)Random -CNFs are Hard for Cutting PlanesJournal of the ACM10.1145/348668069:3(1-32)Online publication date: 27-Jun-2022
https://dl.acm.org/doi/10.1145/3486680
Sleegers Jvan den Berg D(2022)The Hardest Hamiltonian Cycle Problem Instances: The Plateau of Yes and the Cliff of NoSN Computer Science10.1007/s42979-022-01256-03:5Online publication date: 15-Jul-2022
https://dl.acm.org/doi/10.1007/s42979-022-01256-0
Vyas NWilliams R(2021)On Super Strong ETHJournal of Artificial Intelligence Research10.1613/jair.1.1185970(473-495)Online publication date: 1-May-2021
https://dl.acm.org/doi/10.1613/jair.1.11859
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Index Terms

Generating hard satisfiability problems
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
  2. Symbolic and algebraic manipulation
    1. Symbolic and algebraic algorithms
      1. Theorem proving algorithms
2. Theory of computation
  1. Computational complexity and cryptography
  2. Logic
    1. Proof theory

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Information

Published In

Artificial Intelligence Volume 81, Issue 1-2

Special volume on frontiers in problem solving: phase transitions and complexity

March 1996

55 pages

ISSN:0004-3702

Editors:
Daniel G. Bobrow
Xerox Palo Alto Research Center, Palo Alto, CA
,
Tad Hogg
Xerox Palo Alto Research Center, Palo Alto, CA
,
Bernardo A. Huberman
Xerox Palo Alto Research Center, Palo Alto, CA
,
Colin P. Williams
Stanford Univ., Stanford, CA

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Publisher

Elsevier Science Publishers Ltd.

United Kingdom

Publication History

Published: 01 March 1996

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Fleming NPankratov DPitassi TRobere R(2022)Random -CNFs are Hard for Cutting PlanesJournal of the ACM10.1145/348668069:3(1-32)Online publication date: 27-Jun-2022
https://dl.acm.org/doi/10.1145/3486680
Sleegers Jvan den Berg D(2022)The Hardest Hamiltonian Cycle Problem Instances: The Plateau of Yes and the Cliff of NoSN Computer Science10.1007/s42979-022-01256-03:5Online publication date: 15-Jul-2022
https://dl.acm.org/doi/10.1007/s42979-022-01256-0
Vyas NWilliams R(2021)On Super Strong ETHJournal of Artificial Intelligence Research10.1613/jair.1.1185970(473-495)Online publication date: 1-May-2021
https://dl.acm.org/doi/10.1613/jair.1.11859
Omelchenko OBulatov A(2021)Satisfiability threshold for power law random 2-SAT in configuration modelTheoretical Computer Science10.1016/j.tcs.2021.07.028888:C(70-94)Online publication date: 4-Oct-2021
https://dl.acm.org/doi/10.1016/j.tcs.2021.07.028
Xu CLi WWang JYang Y(2021)An improved algorithm for the -MaxSAT problem: asking branchings to satisfy the clausesJournal of Combinatorial Optimization10.1007/s10878-019-00421-142:3(524-542)Online publication date: 1-Oct-2021
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Kordon FHillah LHulin-Hubard FJezequel LPaviot-Adet E(2021)Study of the efficiency of model checking techniques using results of the MCC from 2015 To 2019International Journal on Software Tools for Technology Transfer (STTT)10.1007/s10009-021-00615-123:6(931-952)Online publication date: 1-Dec-2021
https://dl.acm.org/doi/10.1007/s10009-021-00615-1
Yehuda GGabel MSchuster ADaumé HSingh A(2020)It's not what machines can learn, it's whatwe cannot teachProceedings of the 37th International Conference on Machine Learning10.5555/3524938.3525942(10831-10841)Online publication date: 13-Jul-2020
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Kuo YKatz BBarbu A(2020)Encoding formulas as deep networks: Reinforcement learning for zero-shot execution of LTL formulas2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)10.1109/IROS45743.2020.9341325(5604-5610)Online publication date: 24-Oct-2020
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Juma NDietl WTripunitara M(2020)A computational complexity analysis of tunable type inference for Generic Universe TypesTheoretical Computer Science10.1016/j.tcs.2020.01.035814:C(189-209)Online publication date: 24-Apr-2020
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Amendola GRicca FTruszczynski M(2020)New models for generating hard random boolean formulas and disjunctive logic programsArtificial Intelligence10.1016/j.artint.2019.103185279:COnline publication date: 1-Feb-2020
https://dl.acm.org/doi/10.1016/j.artint.2019.103185
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Recommendations

A satisfiability procedure for quantified boolean formulae

On the performance of MaxSAT and MinSAT solvers on 2SAT-MaxOnes

A continuous–discontinuous second-order transition in the satisfiability of random Horn-SAT formulas

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