SINERGY: A Linear Planner Based on Genetic Programming

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  author =       "Ion Muslea",
  title =        "SINERGY: A Linear Planner Based on Genetic
  booktitle =    "Fourth European Conference on Planning",
  year =         "1997",
  editor =       "Sam Steel and Rachid Alami",
  volume =       "1348",
  series =       "Lecture notes in artificial intelligence",
  address =      "Toulouse, France",
  month =        "24--26 " # sep,
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-63912-8",
  URL =          "",
  URL =          "",
  DOI =          "doi:10.1007/3-540-63912-8_95",
  size =         "13 pages",
  abstract =     "we describe SYNERGY, which is a highly parallelizable,
                 linear planning system that is based on the genetic
                 programming paradigm. Rather than reasoning about the
                 world it is planning for, SYNERGY uses artificial
                 selection, recombination and fitness measure to
                 generate linear plans that solve conjunctive goals. We
                 ran SYNERGY on several domains (e.g., the briefcase
                 problem and a few variants of the robot navigation
                 problem), and the experimental results show that our
                 planner is capable of handling problem instances that
                 are one to two orders of magnitude larger than the ones
                 solved by UCPOP. In order to facilitate the search
                 reduction and to enhance the expressive power of
                 SYNERGY, we also propose two major extensions to our
                 planning system: a formalism for using hierarchical
                 planning operators, and a framework for planning in
                 dynamic environments.",
  notes =        "ECP'97",

Genetic Programming entries for Ion Muslea