Reinforcement Programming for function approximation
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- @InProceedings{Rana:2012:UKCI,
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author = "Salah Rana and Malcolm Crowe and Colin Fyfe",
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booktitle = "12th UK Workshop on Computational Intelligence (UKCI
2012)",
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title = "Reinforcement Programming for function approximation",
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year = "2012",
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month = "5-7 " # sep,
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address = "Edinburgh",
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isbn13 = "978-1-4673-4391-6",
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DOI = "doi:10.1109/UKCI.2012.6335777",
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size = "5 pages",
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abstract = "Reinforcement learning is one of the major strands of
current computational intelligence: it is used to
enable an agent to explore an environment in order to
ascertain the best actions in that environment. Genetic
programming is a method to evolve programs and given
the similarity between genetic algorithms and
reinforcement learning, it is perhaps surprising that
so little attention has been given to using
reinforcement learning to identify useful programs.
This paper makes a start on this task by investigating
using reinforcement learning methods for function
approximation.",
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keywords = "genetic algorithms, genetic programming, function
approximation, learning (artificial intelligence),
computational intelligence, function approximation,
reinforcement learning, reinforcement programming,
Equations, Function approximation, Learning,
Mathematical model, Programming profession",
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notes = "Also known as \cite{6335777}",
- }
Genetic Programming entries for
Salah Aziz Rana
Malcolm Crowe
Colin Fyfe
Citations