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Unwitting distributed genetic programming via asynchronous JavaScript and XML

Published: 07 July 2007 Publication History

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.

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cover image ACM Conferences
GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation
July 2007
2313 pages
ISBN:9781595936974
DOI:10.1145/1276958
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 07 July 2007

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Author Tags

  1. AJAX
  2. JavaScript
  3. Push
  4. PushGP
  5. XML
  6. networking
  7. stack-based genetic programming

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GECCO '07 Paper Acceptance Rate 266 of 577 submissions, 46%;
Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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  • (2019)PandoProceedings of the 20th International Middleware Conference10.1145/3361525.3361539(96-109)Online publication date: 9-Dec-2019
  • (2019)JSDoop and TensorFlow.js: Volunteer Distributed Web Browser-Based Neural Network TrainingIEEE Access10.1109/ACCESS.2019.29502877(158671-158684)Online publication date: 2019
  • (2018)Cloudy distributed evolutionary computationProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3205651.3207858(1138-1140)Online publication date: 6-Jul-2018
  • (2018)Increasing Performance via Gamification in a Volunteer-Based Evolutionary Computation SystemInformation Processing and Management of Uncertainty in Knowledge-Based Systems. Applications10.1007/978-3-319-91479-4_29(342-353)Online publication date: 18-May-2018
  • (2017)Browser-based Harnessing of Voluntary Computational PowerFoundations of Computing and Decision Sciences10.1515/fcds-2017-000142:1(3-42)Online publication date: 4-Mar-2017
  • (2017)Faster GPU-based genetic programming using a two-dimensional stackSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-016-2034-021:14(3859-3878)Online publication date: 1-Jul-2017
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  • (2016)Cloudy Distributed Evolutionary AlgorithmsProceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion10.1145/2908961.2926999(819-821)Online publication date: 20-Jul-2016
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