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On the use of context sensitive grammars in grammatical evolution for legal non-compliance detection

Published:13 July 2019Publication History

ABSTRACT

We extend the context-free grammar mapping method in the Grammatical Evolution search heuristic. Grammatical Evolution guarantees the generation of transparent and syntactically correct sentences(phenotypes), but not necessarily semantically correct or feasible ones. Generating syntactically valid phenotypes with postprocessing to filter out semantically invalid ones suffers from some issues, e.g. introduction of bias toward short phenotypes and loss in search efficiency. These issues become significant in legal application domains. We first demonstrate that applying Grammatical Evolution with a context free grammar to legal non-compliance detection problems might not be a tenable solution. Then we demonstrate how the addition of context sensitivity improves both the search efficiency and achieves a greater diversity in the case of the iBoB problem regarding legal non-compliance.

References

  1. Erik Hemberg, Jacob Rosen, Geoff Warner, Sanith Wijesinghe, and Una-May O'Reilly. 2016. Detecting tax evasion: a co-evolutionary approach. Artificial Intelligence and Law 24, 2 (2016), 149--182. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. On the use of context sensitive grammars in grammatical evolution for legal non-compliance detection

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      cover image ACM Conferences
      GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion
      July 2019
      2161 pages
      ISBN:9781450367486
      DOI:10.1145/3319619

      Copyright © 2019 ACM

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      New York, NY, United States

      Publication History

      • Published: 13 July 2019

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