SATLIB: An Online Resource for Research on SAT
By Holger H. Hoos, Thomas Stützle, Ian P. Gent, Hans van Maaren, Thomas J. Walsh. 2000
462 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/5a826febdca350f698c6e269e62479eee9ef9f38
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Citations in the corpus
- Chapter 3 – The Cross-Entropy Method for Optimization (2013, methodology): “As a specific example we consider the SAT instance uf75-01 from Hoos and Stützle (2000). To illustrate the role of the sampling distribution, we first use the same method of generation as in the knapsack problem; that is, at each iteration t the j-th component of X is generated according to a Ber(v̂”
- Combinatorial Optimization with Graph Convolutional Networks and Guided Tree Search (2018, methodology): “For training, we use the SATLIB benchmark [21].”
- RevLib: An Online Resource for Reversible Functions and Reversible Circuits (2008, methodology): “The benefits of widely used benchmark collections have already been seen e.g. in the circuit domain with ISCAS benchmarks [4], in the area of Boolean satisfiability by SATLIB [9] and by TSPLIB [15] for the traveling salesman problem.”
- Introducing StarExec: a Cross-Community Infrastructure for Logic Solving (2014, background): “This includes standard input/output formats for solvers, e.g., [3, 14]; libraries of benchmark problems, e.g., [2, 6, 11, 14]; solver execution services, e.g., [12, 13, 15]; and solver competitions, e.g., [1, 4, 5, 7, 8, 9, 10].”
- The TPTP Problem Library and Associated Infrastructure (2009, background): “There are very few propositional problems—these are of lesser interest to first-order ATP, and are collected by the SAT community [12].”
- The cross-entropy method for estimation (2013, methodology): “As a specific example we consider the SAT instance uf75-01 from Hoos and Stützle (2000). To illustrate the role of the sampling distribution, we first use the same method of generation as in the knapsack problem; that is, at each iteration t the j-th component of X is generated according to a Ber(v̂”