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Assessing different architectures for evolutionary algorithms in javascript

Published: 12 July 2014 Publication History

Abstract

JavaScript (JS) is nowadays the only language that can be used to develop web-based client-server applications in both tiers, client and server. This makes it an interesting choice for developing distributed evolutionary computation experiments, but the best way from algorithmic and practical point of views is not clear, so we will compare different distributed EC architectures in JavaScript using NodEO, an open source JS framework released by us.

References

[1]
D. H. Ackley. A connectionist machine for genetic hillclimbing. Kluwer Academic Publishers, Norwell, MA, USA, 1987.
[2]
J. J. Merelo Guervós. NodEO, a evolutionary algorithm library in Node. Technical report, GeNeura group, Mar. 2014. Available at http://figshare.com/articles/nodeo/972892.

Cited By

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  • (2024)Green Evolutionary Algorithms and JavaScript: A Study on Different Software and Hardware ArchitecturesSoftware Technologies10.1007/978-3-031-61753-9_1(1-18)Online publication date: 24-May-2024

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Published In

cover image ACM Conferences
GECCO Comp '14: Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation
July 2014
1524 pages
ISBN:9781450328814
DOI:10.1145/2598394
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 July 2014

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Author Tags

  1. asynchronous evolution
  2. javascript
  3. node.js
  4. parallel evolutionary algorithms

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GECCO '14
Sponsor:
GECCO '14: Genetic and Evolutionary Computation Conference
July 12 - 16, 2014
BC, Vancouver, Canada

Acceptance Rates

GECCO Comp '14 Paper Acceptance Rate 180 of 544 submissions, 33%;
Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

View all
  • (2024)Green Evolutionary Algorithms and JavaScript: A Study on Different Software and Hardware ArchitecturesSoftware Technologies10.1007/978-3-031-61753-9_1(1-18)Online publication date: 24-May-2024

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