Exploring and evolving process-oriented control for real and virtual fire fighting robots
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{Hardey:2012:GECCO,
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author = "Kathryn Hardey and Eren Corapcioglu and
Molly Mattis and Mark Goadrich and Matthew Jadud",
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title = "Exploring and evolving process-oriented control for
real and virtual fire fighting robots",
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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 = "105--112",
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keywords = "genetic algorithms, genetic programming, artificial
life/robotics/evolvable hardware",
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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:10.1145/2330163.2330179",
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publisher = "ACM",
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publisher_address = "New York, NY, USA",
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abstract = "Current research in evolutionary robotics is largely
focused on creating controllers by either evolving
neural networks or refining genetic programs based on
grammar trees. We propose the use of the parallel,
dataflow languages for the construction of effective
robotic controllers and the evolution of new
controllers using genetic programming techniques. These
languages have the advantages of being built on
concurrent execution frameworks that lend themselves to
formal verification along with being visualized as a
dataflow graph. In this paper, we compare and contrast
the development and subsequent evolution of one such
process-oriented control algorithm. Our control
software was built from composable, communicating
processes executing in parallel, and we tested our
solution in an annual fire-fighting robotics
competition. Subsequently, we evolved new controllers
in a virtual simulation of this parallel dataflow
domain, and in doing so discovered and quantified more
efficient solutions. This research demonstrates the
effectiveness of using process networks as the basis
for evolutionary robotics.",
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notes = "Also known as \cite{2330179} 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
Kathryn Hardey
Eren Corapcioglu
Molly Mattis
Mark Goadrich
Matthew Jadud
Citations