Evolutionary Solo Pong Players
Created by W.Langdon from
gp-bibliography.bib Revision:1.8028
- @TechReport{langdon:2005:pongtr,
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author = "W. B. Langdon and Riccardo Poli",
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title = "Evolutionary Solo Pong Players",
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institution = "Department of Computer Science, University of Essex",
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year = "2005",
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number = "CSM-423",
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address = "Colchester, UK",
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month = "17 " # mar,
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keywords = "genetic algorithms, genetic programming, XPS, games,
AI, PSO",
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URL = "http://www.cs.essex.ac.uk/technical-reports/2005/csm423.pdf",
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ISSN = "1744-8050",
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abstract = "An Internet Java Applet
http://www.cs.essex.ac.uk/staff/poli/SoloPong/ allows
users anywhere to play the Solo Pong game. We compare
people's performance to a hand coded ``Optimal'' player
and programs automatically produced by artificial
intelligence. The AI techniques are: genetic
programming, including a hybrid of GP and a human
designed algorithm, and a particle swarm optimiser. The
AI approaches are not fine tuned. GP and PSO find good
players. Evolutionary computation (EC) is able to beat
both human designed code and human players.",
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notes = "Replaced by langdon:2005:CECa",
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size = "18 pages",
- }
Genetic Programming entries for
William B Langdon
Riccardo Poli
Citations