A Methodology for Missile Countermeasures Optimization under Uncertainty

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@Article{Moore:2002:EC,
  author =       "Frank W. Moore",
  title =        "A Methodology for Missile Countermeasures Optimization
                 under Uncertainty",
  journal =      "Evolutionary Computation",
  year =         "2002",
  volume =       "10",
  number =       "2",
  pages =        "129--149",
  month =        "Summer",
  keywords =     "genetic algorithms, genetic programming",
  ISSN =         "1063-6560",
  DOI =          "doi:10.1162/106365602320169820",
  abstract =     "The missile countermeasures optimization problem is a
                 complex strategy optimization problem that combines
                 aircraft maneuvers with additional countermeasures in
                 an attempt to survive attack from a single
                 surface-launched, anti-aircraft missile. Classic
                 solutions require the evading aircraft to execute
                 specific sequences of maneuvers at precise distances
                 from the pursuing missile and do not effectively
                 account for uncertainty about the type and/or current
                 state of the missile. This paper defines a new
                 methodology for solving the missile countermeasures
                 optimization problem under conditions of uncertainty.
                 The resulting genetic programming system evolves
                 programs that combine maneuvers with such
                 countermeasures as chaff, flares, and jamming to
                 optimize aircraft survivability. This methodology may
                 be generalized to solve strategy optimization problems
                 for intelligent, autonomous agents operating under
                 conditions of uncertainty.",
  notes =        "Department of Computer Science and Systems Analysis,
                 Miami University, 230 Kreger Hall, Oxford, Ohio 45056,
                 USA",
}

Genetic Programming entries for Frank William Moore

Citations