Parallel and Distributed Computational Intelligence

Created by W.Langdon from gp-bibliography.bib Revision:1.2031

@Book{FernandezdeVega:pdci,
  editor =       "Francisco {Fernandez de Vega} and Erick Cantu-Paz",
  title =        "Parallel and Distributed Computational Intelligence",
  publisher =    "Springer",
  year =         "2010",
  volume =       "269",
  series =       "Studies in Computational Intelligence",
  edition =      "1st",
  keywords =     "genetic algorithms, genetic programming, Parallel
                 Computing, Distributed Computing, Grid Computing",
  isbn13 =       "978-3-642-10674-3",
  URL =          "http://www.springer.com/engineering/mathematical/book/978-3-642-10674-3",
  doi =          "doi:10.1007/978-3-642-10675-0",
  abstract =     "The growing success of biologically inspired
                 algorithms in solving large and complex problems has
                 spawned many interesting areas of research. Over the
                 years, one of the mainstays in bio-inspired research
                 has been the exploitation of parallel and distributed
                 environments to speedup computations and to enrich the
                 algorithms. From the early days of research on
                 bio-inspired algorithms, their inherently parallel
                 nature was recognised and different parallelisation
                 approaches have been explored. Parallel algorithms
                 promise reductions in execution time and open the door
                 to solve increasingly larger problems. But parallel
                 platforms also inspire new bio-inspired parallel
                 algorithms that, while similar to their sequential
                 counterparts, explore search spaces differently and
                 offer improvements in solution quality.

                 The objective in editing this book was to assemble a
                 sample of the best work in parallel and distributed
                 biologically inspired algorithms. The editors invited
                 researchers in different domains to submit their work.
                 They aimed to include diverse topics to appeal to a
                 wide audience. Some of the chapters summarise work that
                 has been ongoing for several years, while others
                 describe more recent exploratory work. Collectively,
                 these works offer a global snapshot of the most recent
                 efforts of bioinspired algorithms researchers aiming at
                 profiting from parallel and distributed computer
                 architectures including GPUs, Clusters, Grids,
                 volunteer computing and p2p networks as well as
                 multi-core processors. This volume will be of value to
                 a wide set of readers, including, but not limited to
                 specialists in Bioinspired Algorithms, Parallel and
                 Distributed Computing, as well as computer science
                 students trying to figure out new paths towards the
                 future of computational intelligence.",
  size =         "354 pages",
}

Genetic Programming entries for Francisco Fernandez de Vega Erick Cantu-Paz