Autonomous and cooperative robotic behavior based on fuzzy logic and genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Article{Smith3:2007:ICAE,
  author =       "James F. {Smith III} and ThanhVu H. Nguyen",
  title =        "Autonomous and cooperative robotic behavior based on
                 fuzzy logic and genetic programming",
  journal =      "Integrated Computer-Aided Engineering",
  year =         "2007",
  volume =       "14",
  number =       "2",
  pages =        "141--159",
  keywords =     "genetic algorithms, genetic programming",
  ISSN =         "1069-2509",
  URL =          "http://www.cs.umd.edu/~tnguyen/Pub/acrbbflgp.pdf",
  URL =          "http://content.iospress.com/articles/integrated-computer-aided-engineering/ica00257",
  size =         "19 pages",
  abstract =     "Advances in a fuzzy decision theory that allow
                 automatic cooperation between unmanned aerial vehicles
                 (UAVs) are discussed. The algorithms determine points
                 the UAVs are to sample, flight paths, and the optimal
                 UAVs for the task and related changes during the
                 mission. Human intervention is not required after the
                 mission begins. The algorithms take into account what
                 is known before and during the mission about UAV
                 reliability, fuel, and kinematics as well as the
                 measurement space's meteorological states, terrain, air
                 traffic, threats and related uncertainties. The fuzzy
                 decision tree for path assignment is a significant
                 advance over an older fuzzy decision rule that was
                 previously introduced. Simulations show the ability of
                 the control algorithm to allow UAVs to effectively
                 cooperate to increase the UAV team's likelihood of
                 successfully measuring the atmospheric index of
                 refraction over a large volume. A genetic program (GP)
                 based data mining procedure is discussed for
                 automatically evolving fuzzy decision trees. The GP is
                 used to automatically create the fuzzy decision tree
                 for real-time UAV path assignments. The GP based
                 procedure offers several significant advances over
                 previously introduced GP based data mining procedures.
                 These advances help produce mathematically concise
                 fuzzy decision trees that are consistent with human
                 intuition.",
  notes =        "Code 5741, Naval Research Laboratory, Washington, DC,
                 20375-5320, USA",
}

Genetic Programming entries for James F Smith III ThanhVu Nguyen

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