Parameter tuning of evolutionary reactions systems
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- @InProceedings{Castelli:2012:GECCO,
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author = "Mauro Castelli and Luca Manzoni and
Leonardo Vanneschi",
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title = "Parameter tuning of evolutionary reactions systems",
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booktitle = "GECCO '12: Proceedings of the fourteenth international
conference on Genetic and evolutionary computation
conference",
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year = "2012",
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editor = "Terry Soule and Anne Auger and Jason Moore and
David Pelta and Christine Solnon and Mike Preuss and
Alan Dorin and Yew-Soon Ong and Christian Blum and
Dario Landa Silva and Frank Neumann and Tina Yu and
Aniko Ekart and Will Browne and Tim Kovacs and
Man-Leung Wong and Clara Pizzuti and Jon Rowe and Tobias Friedrich and
Giovanni Squillero and Nicolas Bredeche and
Stephen L. Smith and Alison Motsinger-Reif and Jose Lozano and
Martin Pelikan and Silja Meyer-Nienberg and
Christian Igel and Greg Hornby and Rene Doursat and
Steve Gustafson and Gustavo Olague and Shin Yoo and
John Clark and Gabriela Ochoa and Gisele Pappa and
Fernando Lobo and Daniel Tauritz and Jurgen Branke and
Kalyanmoy Deb",
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isbn13 = "978-1-4503-1177-9",
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pages = "727--734",
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keywords = "genetic algorithms, genetic programming",
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month = "7-11 " # jul,
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organisation = "SIGEVO",
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address = "Philadelphia, Pennsylvania, USA",
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DOI = "doi:10.1145/2330163.2330265",
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publisher = "ACM",
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publisher_address = "New York, NY, USA",
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abstract = "Reaction systems is a formalism inspired by chemical
reactions introduced by Rozenberg and Ehrenfeucht.
Recently, an evolutionary algorithm based on this
formalism, called Evolutionary Reaction Systems, has
been presented. This new algorithm proved to have
comparable performances to other well-established
machine learning methods, like genetic programming,
neural networks and support vector machines on both
artificial and real-life problems. Even if the results
are encouraging, to make Evolutionary Reaction Systems
an established evolutionary algorithm, an in depth
analysis of the effect of its parameters on the search
process is needed, with particular focus on those
parameters that are typical of Evolutionary Reaction
Systems and do not have a counterpart in traditional
evolutionary algorithms. Here we address this problem
for the first time. The results we present show that
one particular parameter, between the ones tested, has
a great influence on the performances of Evolutionary
Reaction Systems, and thus its setting deserves
practitioners' particular attention: the number of
symbols used to represent the reactions that compose
the system. Furthermore, this work represents a first
step towards the definition of a set of default
parameter values for Evolutionary Reaction Systems,
that should facilitate their use for beginners or
inexpert practitioners.",
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notes = "Also known as \cite{2330265} GECCO-2012 A joint
meeting of the twenty first international conference on
genetic algorithms (ICGA-2012) and the seventeenth
annual genetic programming conference (GP-2012)",
- }
Genetic Programming entries for
Mauro Castelli
Luca Manzoni
Leonardo Vanneschi
Citations