The difficulty of roving eyes

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Reynolds:1994:eye,
  author =       "Craig W. Reynolds",
  title =        "The difficulty of roving eyes",
  booktitle =    "Proceedings of the 1994 IEEE World Congress on
                 Computational Intelligence",
  year =         "1994",
  volume =       "1",
  pages =        "262--267",
  address =      "Orlando, Florida, USA",
  month =        "27-29 " # jun,
  publisher =    "IEEE Press",
  DOI =          "doi:10.1109/ICEC.1994.350005",
  keywords =     "genetic algorithms, genetic programming, controller
                 evolution, corridor following task, dynamic aiming,
                 evolved control programs, fitness distributions, lens
                 effect, populations, problem difficulty, problem
                 domain, proximity sensor directions, random search,
                 robot-like vehicle, roving eyes, sensor
                 representations, syntactic constraint, user's
                 representation, vehicle control programs, computer
                 vision, mobile robots, path planning,",
  size =         "6 pages",
  abstract =     "Genetic programming (GP) operates on a problem domain
                 through the lens of the user's representation. The
                 difficulty (GP hardness) of an application can depend
                 as much on the representation as on the problem itself.
                 Seemingly small changes of representation can cause
                 significant changes in difficulty. An example of this
                 effect was discovered while using GP to evolve a
                 controller for a robot-like vehicle performing a
                 corridor-following task. A small syntactic constraint
                 applied to evolved control programs significantly
                 reduced the difficulty of the problem. This allowed a
                 solution to be found with a population of 2000 for a
                 problem that had previously resisted solution with
                 populations of 10,000. The syntactic constraint
                 corresponded to removing the controller's ability to
                 dynamically aim its proximity sensors. In the
                 constrained case, sensor directions remain fixed during
                 the lifetime of the controller and are aimed solely by
                 evolution. In his investigation of the lens effect,
                 Koza (1992) found that the relative difficulty of two
                 representations can be determined by comparing the
                 distribution of fitnesses found during a random search
                 of the two program spaces. Indeed, by examining the
                 initial, random generation of GP runs for the
                 corridor-following problem, we see a foreshadowing of
                 the subsequent difficulty of several sensor
                 representations",
  notes =        "The difficulty for GP to produce a corridor following
                 robot controller is found to depend dramatically on how
                 the sensor primitive ``look-for-obstacle'' is used by
                 GP. With no constraints very difficult. Readily solved
                 if syntax rules are imposed which force its argument to
                 be a constant.",
}

Genetic Programming entries for Craig W Reynolds

Citations