Toward Self-adaptive Embedded Systems: Multi-objective Hardware Evolution

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Paul Kaufmann and Marco Platzner",
  title =        "Toward Self-adaptive Embedded Systems: Multi-objective
                 Hardware Evolution",
  booktitle =    "20th International Conference on Architecture of
                 Computing Systems (ARCS 2007)",
  year =         "2007",
  editor =       "Paul Lukowicz and Lothar Thiele and Gerhard Troester",
  volume =       "4415",
  series =       "LNCS",
  pages =        "199--208",
  address =      "Zurich, Switzerland",
  month =        mar # " 12-15",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, Cartesian
                 Genetic Programming",
  isbn13 =       "978-3-540-71270-1",
  DOI =          "doi:10.1007/978-3-540-71270-1_15",
  size =         "10 pages",
  abstract =     "Evolutionary hardware design reveals the potential to
                 provide autonomous systems with self-adaptation
                 properties. We first outline an architectural concept
                 for an intrinsically evolvable embedded system that
                 adapts to slow changes in the environment by simulated
                 evolution, and to rapid changes in available resources
                 by switching to preevolved alternative circuits. In the
                 main part of the paper, we treat evolutionary circuit
                 design as a multi-objective optimization problem and
                 compare two multi-objective optimizers with a reference
                 genetic algorithm. In our experiments, the best results
                 were achieved with TSPEA2, an optimizer that prefers a
                 single objective while trying to maintain diversity.",
  notes =        "Hashing Function",

Genetic Programming entries for Paul Kaufmann Marco Platzner