Evolving Software with Multiple Outputs and Multiple Populations

Created by W.Langdon from gp-bibliography.bib Revision:1.4216

  author =       "John Hart and Martin Shepperd",
  title =        "Evolving Software with Multiple Outputs and Multiple
  institution =  "School of Design, Engineering and Computing,
                 Bournemouth University",
  year =         "2002",
  number =       "TR02-06",
  address =      "Royal London House, Christchurch Rd, Bournemouth, BH1
                 3LT, UK",
  month =        jul,
  keywords =     "genetic algorithms, genetic programming, evolutionary
                 algorithms, search, embedded system",
  URL =          "http://dec.bournemouth.ac.uk/ESERG/Technical_Reports/TR02-06/TR02-06.pdf",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=",
  size =         "6 pages",
  abstract =     "In this research we are concerned with the automatic
                 evolution of programs for control applications, the
                 particular example we use being software for a simple
                 fridge device with two inputs and three outputs. By
                 careful choice of the target programming language - in
                 a similar vein to a RISC processor - we are able to
                 represent programs as variable length strings and use
                 evolutionary computing techniques to search for fitter
                 individuals. We used a fitness function that summed the
                 fitness of each output channel, by various methods, in
                 an attempt to encourage a total solution using a single
                 population of candidate solutions. In general we were
                 able to successfully evolve suitable solutions,
                 however, the search sometimes suffered from premature
                 convergence once the functionality for two out of the
                 three output channels had evolved. More complex fitness
                 assessment schemes, using mechanisms such as
                 dynamically modifying the fitness associated with an
                 output channel without additional benefit. These
                 difficulties in attempting to do too much with a single
                 population pointed to a `divide and conquer' approach
                 whereby one (or more) populations are dedicated to
                 solving for one output channel alone - whilst being
                 exposed to all inputs. This is seen to be an acceptable
                 approach due to the growth in multi-tasking operating
                 systems and multiprocessor platforms.",
  notes =        "as \cite{hart:2002:gecco:lbp}",

Genetic Programming entries for John Hart Martin J Shepperd