Universal Induction with Varying Sets of Combinators

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@InProceedings{Potapov:2013:AGI,
  author =       "Alexey Potapov and Sergey Rodionov",
  title =        "Universal Induction with Varying Sets of Combinators",
  booktitle =    "Proceedings of the 6th International Conference on
                 Artificial General Intelligence (AGI 2013)",
  year =         "2013",
  editor =       "Kai-Uwe Kuehnberger and Sebastian Rudolph and 
                 Pei Wang",
  volume =       "7999",
  series =       "Lecture Notes in Computer Science",
  pages =        "88--97",
  address =      "Beijing, China",
  month =        jul # " 31-" # aug # " 3",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-642-39520-8",
  DOI =          "doi:10.1007/978-3-642-39521-5_10",
  URL =          "http://dx.doi.org/10.1007/978-3-642-39521-5_10",
  bibsource =    "OAI-PMH server at export.arxiv.org",
  oai =          "oai:arXiv.org:1306.0095",
  URL =          "http://arxiv.org/abs/1306.0095",
  size =         "10 pages",
  abstract =     "Universal induction is a crucial issue in AGI. Its
                 practical applicability can be achieved by the choice
                 of the reference machine or representation of
                 algorithms agreed with the environment. This machine
                 should be updatable for solving subsequent tasks more
                 efficiently. We study this problem on an example of
                 combinatory logic as the very simple Turing-complete
                 reference machine, which enables modifying program
                 representations by introducing different sets of
                 primitive combinators. Genetic programming system is
                 used to search for combinator expressions, which are
                 easily decomposed into sub-expressions being recombined
                 in crossover. Our experiments show that low-complexity
                 induction or prediction tasks can be solved by the
                 developed system (much more efficiently than using
                 brute force); useful combinators can be revealed and
                 included into the representation simplifying more
                 difficult tasks. However, optimal sets of combinators
                 depend on the specific task, so the reference machine
                 should be adaptively chosen in coordination with the
                 search engine.",
  notes =        "oai:arXiv.org:1306.0095,",
}

Genetic Programming entries for Alexey Potapov Sergey Rodionov

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