Unwitting distributed genetic programming via asynchronous JavaScript and XML

Created by W.Langdon from gp-bibliography.bib Revision:1.2469

@InProceedings{1277282,
  author =       "Jon Klein and Lee Spector",
  title =        "Unwitting distributed genetic programming via
                 asynchronous {JavaScript} and {XML}",
  booktitle =    "GECCO '07: Proceedings of the 9th annual conference on
                 Genetic and evolutionary computation",
  year =         "2007",
  editor =       "Dirk Thierens and Hans-Georg Beyer and 
                 Josh Bongard and Jurgen Branke and John Andrew Clark and 
                 Dave Cliff and Clare Bates Congdon and Kalyanmoy Deb and 
                 Benjamin Doerr and Tim Kovacs and Sanjeev Kumar and 
                 Julian F. Miller and Jason Moore and Frank Neumann and 
                 Martin Pelikan and Riccardo Poli and Kumara Sastry and 
                 Kenneth Owen Stanley and Thomas Stutzle and 
                 Richard A Watson and Ingo Wegener",
  volume =       "2",
  isbn13 =       "978-1-59593-697-4",
  pages =        "1628--1635",
  address =      "London",
  URL =          "http://www.cs.bham.ac.uk/~wbl/biblio/gecco2007/docs/p1628.pdf",
  doi =          "doi:10.1145/1276958.1277282",
  publisher =    "ACM Press",
  publisher_address = "New York, NY, USA",
  month =        "7-11 " # jul,
  organisation = "ACM SIGEVO (formerly ISGEC)",
  keywords =     "genetic algorithms, genetic programming, AJAX,
                 JavaScript, networking, push, PushGP, stack based
                 genetic programming, XML",
  abstract =     "The success of a genetic programming system in solving
                 a problem is often a function of the available
                 computational resources. For many problems, the larger
                 the population size and the longer the genetic
                 programming run the more likely the system is to find a
                 solution. In order to increase the probability of
                 success on difficult problems, designers and users of
                 genetic programming systems often desire access to
                 distributed computation, either locally or across the
                 Internet, to evaluate fitness cases more quickly. Most
                 systems for internet-scale distributed computation
                 require a user's explicit participation and the
                 installation of client side software. We present a
                 proof-of-concept system for distributed computation of
                 genetic programming via asynchronous JavaScript and XML
                 (AJAX) techniques which requires no explicit user
                 interaction and no installation of client side
                 software. Clients automatically and possibly even
                 unknowingly participate in a distributed genetic
                 programming system simply by visiting a webpage,
                 thereby allowing for the solution of genetic
                 programming problems without running a single local
                 fitness evaluation. The system can be easily introduced
                 into existing webpages to exploit unused client-side
                 computation for the solution of genetic programming and
                 other problems.",
  notes =        "GECCO-2007 A joint meeting of the sixteenth
                 international conference on genetic algorithms
                 (ICGA-2007) and the twelfth annual genetic programming
                 conference (GP-2007).

                 ACM Order Number 910071",
}

Genetic Programming entries for Jon Klein Lee Spector