- author = "Andreas Ronge and Mats G. Nordahl",
- title = "Genetic Programs and Co-Evolution Developing robust general purpose controllers using local mating in two dimensional populations",
- booktitle = "Parallel Problem Solving from Nature IV, Proceedings of the International Conference on Evolutionary Computation",
- year = "1996",
- editor = "Hans-Michael Voigt and Werner Ebeling and Ingo Rechenberg and Hans-Paul Schwefel",
- series = "LNCS",
- volume = "1141",
- pages = "81--90",
- address = "Berlin, Germany",
- publisher_address = "Heidelberg, Germany",
- month = "22-26 " # sep,
- publisher = "Springer Verlag",
- keywords = "genetic algorithms, genetic programming",
- ISBN = "3-540-61723-X",
-
DOI = "
doi:10.1007/3-540-61723-X_972",
- size = "10 pages",
-
abstract = "
A co-evolutionary approach for developing programs for controlling a very simple {"}robot-like{"} simulated vehicle is presented. The main goal is to find programs that can generalize and solve other similar problems. Good results are achieved by co-evolving the test cases and the simulated vehicles and using locality in both the reproduction and evaluation phases. The fitness of a controller is determined by its performance in competition with its neighbours in the test case population. The fitness of a test case is similarly determined through competition with its neighbours in the controller population. The co-evolved controllers are more robust and general than a simple hand-designed algorithm or controllers evolved using a fixed training set.",
- notes = "http://lautaro.fb10.tu-berlin.de/ppsniv.html PPSN4 256 indexed memory cells, single ADF, depth restriction. Mentions {"}guided crossover{"} ?how directed? {"}The introduction of geographic separation tends to improve population diversity{"}",
