Unwitting Distributed Genetic Programming

via Asynchronous JavaScript and XML

Block diagram of unwitting distributed GP

Jon Klein (jklein@artificial.com)
Lee Spector (lspector@hampshire.edu, http://hampshire.edu/lspector)


This page contains material related to "Unwitting Distributed Genetic Programming via Asynchronous JavaScript and XML," a paper in the Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2007), published by The Association of Computing Machinery.


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.

Citation

Klein, J. and L. Spector. 2007. Unwitting Distributed Genetic Programming via Asynchronous JavaScript and XML. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2007), pp. 1628-1635, New York, NY: The Association of Computing Machinery.

Full paper

Full paper in PDF format: http://hampshire.edu/lspector/pubs/unwitting-gecco-2007.pdf (192KB).

Presentation Slides

Prepared for the GECCO 2007 conference: http://hampshire.edu/lspector/db-gecco-2007/unwitting-gecco-2007/unwitting-gecco-2007-presentation.pdf (2.9MB).

Demo

Interactive PushScript demo: http://www.spiderland.org/PushScript

More Information

Evolutionary computing with the Push programming language: http://hampshire.edu/lspector/push.html

Acknowledgments

This material is based upon work supported by the U.S. National Science Foundation under Grant No. 0308540. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the NSF.