Lossless compression via two-level logic minimization: a case study using Chess endgame data (2020)

by Dave Gomboc and Christian R. Shelton

Abstract: The utililty of processing techniques long in use within the electronic design automation community is underappreciated within the artificial intelligence community. We update and use the ESPRESSO logic minimizer in order to generate an exact, readily-queryable, and succinct representation of voluminous Chess endgame data.

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Dave Gomboc and Christian R. Shelton (2020). "Lossless compression via two-level logic minimization: a case study using Chess endgame data." 29th International Workshop on Logic and Synthesis. Version here corrects minor error in number of clauses for KN versus k.

Bibtex citation

@inproceedings{GomShe20,
   author = "Dave Gomboc and Christian R. Shelton",
   title = "Lossless compression via two-level logic minimization: a case study using Chess endgame data",
   booktitle = "29th International Workshop on Logic and Synthesis",
      booktitleabbr = "IWLS",
       year = 2020,
}

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