Cellular Encoding for Interactive Evolutionary Robotics

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

@TechReport{gruau:1996:ceier,
  author =       "Frederic Gruau and Kameel Quatramaran",
  title =        "Cellular Encoding for Interactive Evolutionary
                 Robotics",
  institution =  "School of Cognitive and Computing Sciences, University
                 of Sussex",
  year =         "1996",
  type =         "Cognitive Science Research Paper",
  number =       "425",
  address =      "Falmer, Brighton, Sussex, UK",
  month =        jul,
  keywords =     "genetic algorithms, genetic programming",
  URL =          "ftp://ftp.cogs.susx.ac.uk/pub/reports/csrp/csrp425.ps.Z",
  URL =          "http://www.cogs.susx.ac.uk/cgi-bin/htmlcogsreps?csrp425",
  abstract =     "This work reports experiments in interactive
                 evolutionary robotics. The goal is to evolve an
                 Artificial Neural Network (ANN) to control the
                 locomotion of an 8-legged robot. The ANNs are encoded
                 using a cellular developmental process called cellular
                 encoding. In a previous work similar experiments have
                 been carried on successfully on a simulated robot. They
                 took however around 1 million different ANN
                 evaluations. In this work the fitness is determined on
                 a real robot, and no more than a few hundreds
                 evaluations can be performed. Various ideas were
                 implemented so as to decrease the required number of
                 evaluations from 1 million to 200. First we used cell
                 cloning and link typing. Second we did as many things
                 as possible interactively: interactive problem
                 decomposition, interactive syntactic constraints,
                 interactive fitness. More precisely: 1- A modular
                 design was chosen where a controller for an individual
                 leg, with a precise neuronal interface was developed.
                 2- Syntactic constraints were used to promote useful
                 building blocs and impose an 8-fold symmetry. 3- We
                 determine the fitness interactively by hand. We can
                 reward features that would otherwise be very difficult
                 to locate automatically. Interactive evolutionary
                 robotics turns out to be quite successful, in the first
                 bug-free run a global locomotion controller that is
                 faster than a programmed controller could be evolved.",
  size =         "23 pages",
}

Genetic Programming entries for Frederic Gruau Kameel Quatramaran

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