Summary of Certified Maxsat Preprocessing, by Hannes Ihalainen et al.
Certified MaxSAT Preprocessing
by Hannes Ihalainen, Andy Oertel, Yong Kiam Tan, Jeremias Berg, Matti Järvisalo, Jakob Nordström
First submitted to arxiv on: 26 Apr 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper focuses on ensuring the correctness of maximum satisfiability (MaxSAT) solvers, a key technique for solving NP-hard optimization problems. Building on decades of progress in Boolean satisfiability (SAT) solving, MaxSAT has become a viable approach, but its correctness remains an important concern. The authors demonstrate how pseudo-Boolean proof logging can be used to certify the correctness of modern MaxSAT preprocessing techniques. By combining and extending existing tools, they provide end-to-end proof checking for input and preprocessed output MaxSAT problem instances. An evaluation on applied MaxSAT benchmarks shows that this approach is feasible in practice. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps make sure that computer programs solving complex math problems are correct. These programs can solve really hard problems, but we need to be sure they’re working right. The authors find a way to prove that these programs are doing the right thing by checking their work step by step. They use special tools to show that the input and output of the program are correct. This helps us trust the results from these complex calculations. |
Keywords
» Artificial intelligence » Optimization
