Unwitting distributed genetic programming via asynchronous JavaScript and XML

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 sy...

• Type: Conference
• Year: 2007
• Where: GECCO
• Authors: Jon Klein, Lee Spector
• Keywords: Distributed Computation, Distributed Genetic Programming, GECCO 2007, Genetic Programming