Investigating Multi population Competetive Coevolution for Anticipating of Tax Evasion

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@InProceedings{Hemberg:2016:GPTP,
  author =       "Erik Hemberg and Jacob Rosen and Una-May O'Reilly",
  title =        "Investigating Multi population Competetive Coevolution
                 for Anticipating of Tax Evasion",
  booktitle =    "Genetic Programming Theory and Practice XIV",
  year =         "2016",
  editor =       "Rick Riolo and Bill Worzel and Brian Goldman and 
                 Bill Tozier",
  address =      "Ann Arbor, USA",
  month =        "19-21 " # may,
  publisher =    "Springer",
  note =         "Forthcoming",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-319-97087-5",
  URL =          "https://www.springer.com/us/book/9783319970875",
  abstract =     "We investigate the application of a version of Genetic
                 Programming with grammars, called Grammatical
                 Evolution, and a multi population competitive
                 coevolutionary algorithm for anticipating tax evasion
                 in the domain of U.S. Partnership tax regulations. A
                 problem in tax auditing is that as soon as an evasion
                 scheme is detected a new, slightly mutated, variant of
                 the scheme appears. Multi population competitive
                 coevolutionary algorithms are disposed to explore
                 adversarial problems, such as the arms-race between tax
                 evader and auditor. Furthermore, we use Genetic
                 Programming and grammars to represent and search the
                 transactions of tax evaders and tax audit policies.
                 Grammars are helpful for representing and biasing the
                 search space. The feasibility of the method is explored
                 with an example of adversarial coevolution in tax
                 evasion. We study the dynamics and the solutions of the
                 competing populations in this scenario, and note that
                 we are able to replicate some of the expected
                 behaviour.",
  notes =        "

                 Part of \cite{Tozier:2016:GPTP} to be published after
                 the workshop",
}

Genetic Programming entries for Erik Hemberg Jacob Rosen Una-May O'Reilly

Citations