Reinforcement Programming for function approximation

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@InProceedings{Rana:2012:UKCI,

• author = "Salah Rana and Malcolm Crowe and Colin Fyfe",
• booktitle = "12th UK Workshop on Computational Intelligence (UKCI 2012)",
• title = "Reinforcement Programming for function approximation",
• year = "2012",
• month = "5-7 " # sep,
• address = "Edinburgh",
• isbn13 = "978-1-4673-4391-6",
• DOI = "doi:10.1109/UKCI.2012.6335777",
• size = "5 pages",
• 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.",
• 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",
• notes = "Also known as \cite{6335777}",

}

Genetic Programming entries for Salah Aziz Rana Malcolm Crowe Colin Fyfe

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