Unwitting distributed genetic programming via asynchronous JavaScript and XML
Paper in proceeding, 2007

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. Copyright 2007 ACM.






Stack-based genetic programming



Jon Klein

Chalmers, Energy and Environment, Physical Resource Theory

Hampshire College

Lee Spector

Hampshire College

Proceedings of GECCO 2007: Genetic and Evolutionary Computation Conference


9th Annual Genetic and Evolutionary Computation Conference, GECCO 2007
, United Kingdom,

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Computer Engineering

Computer Science

Computer Systems



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