EvoSpace: a distributed evolutionary platform based on the tuple space model

Published in Conferences Papers
  1. Mario Garc\'ıa-Valdez, Leonardo Trujillo, Francisco Fernández Vega, Juan Julián Merelo Guervós and Gustavo Olague. EvoSpace-Interactive: A Framework to Develop Distributed Collaborative-interactive Evolutionary Algorithms for Artistic Design. In Proceedings of the Second International Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design. 2013, 121–132. URL, DOI BibTeX

    @inproceedings{Garcia-Valdez:2013:EFD:2456598.2456609,
    	author = "Garc\'{\i}a-Valdez, Mario and Trujillo, Leonardo and de Vega, Francisco Fern\'{a}ndez and Merelo Guerv\'{o}s, Juan Juli\'{a}n and Olague, Gustavo",
    	title = "EvoSpace-Interactive: A Framework to Develop Distributed Collaborative-interactive Evolutionary Algorithms for Artistic Design",
    	booktitle = "Proceedings of the Second International Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design",
    	series = "EvoMUSART'13",
    	year = 2013,
    	isbn = "978-3-642-36954-4",
    	location = "Vienna, Austria",
    	pages = "121--132",
    	numpages = 12,
    	url = "http://dx.doi.org/10.1007/978-3-642-36955-1_11",
    	doi = "10.1007/978-3-642-36955-1_11",
    	acmid = 2456609,
    	publisher = "Springer-Verlag",
    	address = "Berlin, Heidelberg",
    	keywords = "cloud computing, collaborative design, evolutionary art, interactive evolution"
    }
    
Abstract

This paper presents EvoSpace, a Cloud service for the development of distributed evolutionary algorithms. EvoSpace is based on the tuple space model, an associatively addressed memory space shared by several processes. Remote clients, called EvoWorkers, connect to EvoSpace and periodically take a subset of individuals from the global population, perform evolutionary operations on them, and return a set of new individuals. Several EvoWorkers carry out the evolutionary search in parallel and asynchronously, interacting with each other through the central repository. EvoSpace is designed to be domain independent and flexible, in the sense that in can be used with different types of evolutionary algorithms and applications. In this paper, a genetic algorithm is tested on the EvoSpace platform using a well-known benchmark problem, achieving promising results compared to a standard evolutionary system.

Published in
Proceedings of the 16Th European Conference on Applications of Evolutionary Computation (EvoApplications'13)
Volume 7835
Pages 499-508
http://link.springer.com/chapter/10.1007%2F978-3-642-37192-9_50
Date of conference
03-05 Abril 2013
ISSN
0302-9743
ISBN
978-3-642-37192-9
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