A Library to Run Evolutionary Algorithms in the Cloud using MapReduce
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InProceedings{fazenda:evoapps12,
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author = "Pedro Fazenda and James McDermott and
Una-May O'Reilly",
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title = "A Library to Run Evolutionary Algorithms in the Cloud
using {MapReduce}",
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booktitle = "Applications of Evolutionary Computing,
EvoApplications2012: {EvoCOMNET}, {EvoCOMPLEX},
{EvoFIN}, {EvoGAMES}, {EvoHOT}, {EvoIASP}, {EvoNUM},
{EvoPAR}, {EvoRISK}, {EvoSTIM}, {EvoSTOC}",
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year = "2012",
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month = "11-13 " # apr,
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editor = "Cecilia {Di Chio} and Alexandros Agapitos and
Stefano Cagnoni and Carlos Cotta and F. {Fernandez de Vega} and
Gianni A. {Di Caro} and Rolf Drechsler and
Aniko Ekart and Anna I Esparcia-Alcazar and Muddassar Farooq and
William B. Langdon and Juan J. Merelo and
Mike Preuss and Hendrik Richter and Sara Silva and
Anabela Simoes and Giovanni Squillero and Ernesto Tarantino and
Andrea G. B. Tettamanzi and Julian Togelius and
Neil Urquhart and A. Sima Uyar and Georgios N. Yannakakis",
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series = "LNCS",
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volume = "7248",
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publisher = "Springer Verlag",
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address = "Malaga, Spain",
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pages = "416--425",
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organisation = "EvoStar",
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keywords = "genetic algorithms, genetic programming, MapReduce,
Hadoop, EC, Amazon EC2, FlexEA",
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isbn13 = "978-3-642-29177-7",
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DOI = "doi:10.1007/978-3-642-29178-4_42",
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size = "10 pages",
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abstract = "We discuss ongoing development of an evolutionary
algorithm library to run on the cloud. We relate how we
have used the Hadoop open-source MapReduce distributed
data processing framework to implement a single
`island' with a potentially very large population. The
design generalises beyond the current, one-off kind of
MapReduce implementations. It is in preparation for the
library becoming a modelling or optimization service in
a service oriented architecture or a development tool
for designing new evolutionary algorithms.",
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notes = "EDO-Lib, Reporter, Island Model, HDFS, p419
'FitnessEvaluator can be set by injection'. Matlab.
Does not give execution time in terms of GP operation
per second. Population up to 1 million. XEN.org p423
'takes much longer to design a MapReduce implementation
than it would to develop a socket or MPI model.' p424
'It also results in a code base which requires more
effort to support and maintain which impacts research
agility.'
Part of \cite{DiChio:2012:EvoApps} EvoApplications2012
held in conjunction with EuroGP2012, EvoCOP2012,
EvoBio'2012 and EvoMusArt2012",
- }
Genetic Programming entries for
Pedro Vicoso Fazenda
James McDermott
Una-May O'Reilly
Citations