Extracting Minimum Unsatisfiable Cores with a Greedy Genetic Algorithm

  title={Extracting Minimum Unsatisfiable Cores with a Greedy Genetic Algorithm},
  author={Jianmin Zhang and Sikun Li and ShengYu Shen},
  booktitle={Australian Conference on Artificial Intelligence},
Explaining the causes of infeasibility of Boolean formulas has practical applications in various fields. We are generally interested in a minimum explanation of infeasibility that excludes irrelevant information. A smallest-cardinality unsatisfiable subset, called a minimum unsatisfiable core, can provide a succinct explanation of infeasibility and is valuable for applications. However little attention has been concentrated on extraction of minimum unsatisfiable cores. In this paper, we propose… 

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A heuristic-based local search algorithm is proposed to derive unsatisfiable cores by directly constructs the resolution sequence for proving unsatisfiability with a local search procedure, and then extracts small unsatisfiability cores from the sequence.

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Finding Unsatisfiable Subformulas with Stochastic Method

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Minimal Unsatisfiability: Models, Algorithms and Applications (Invited Paper)

  • Joao Marques-Silva
  • Computer Science
    2010 40th IEEE International Symposium on Multiple-Valued Logic
  • 2010
This paper provides an overview of some of the computational problems related with minimal unsatisfiability in Boolean logic, including the identification of one minimal unsatisfiable sub-formula and the Identification of all minimal unsatisfable sub- formulas.

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Accelerated Deletion-based Extraction of Minimal Unsatisfiable Cores

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On Computing Minimum Unsatisfiable Cores

As part of the process of generating unsatisfiable proofs, one is also interested in unsatisfiable subformulas of the original formula, also known as unsatisfiable cores, which may be very useful in AI problems where identifying the minimum core is crucial for correcting the minimum amount of inconsistent information.

MUP: a minimal unsatisfiability prover

  • Jinbo Huang
  • Computer Science
    Proceedings of the ASP-DAC 2005. Asia and South Pacific Design Automation Conference, 2005.
  • 2005
This paper describes a practical algorithm that decides the minimal unsatisfiability of any CNF formula through BDD manipulation and provides an empirical evaluation of the algorithm, highlighting its efficiency on a set of hard problems as well as its ability to work with existing subformula extraction tools to achieve optimal results.

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Restoring Satisfiability or Maintaining Unsatisfiability by finding small Unsatisfiable Subformulae

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