Tweaking a tower of blocks leads to a TMBL: Pursuing long term fitness growth in program evolution
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- @InProceedings{Lewis:2010:cec,
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author = "Tony E. Lewis and George D. Magoulas",
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title = "Tweaking a tower of blocks leads to a TMBL: Pursuing
long term fitness growth in program evolution",
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booktitle = "IEEE Congress on Evolutionary Computation (CEC 2010)",
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year = "2010",
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pages = "4465--4472",
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address = "Barcelona, Spain",
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month = "18-23 " # jul,
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publisher = "IEEE Press",
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keywords = "genetic algorithms, genetic programming, TMBL,
evolutionary computation, genetic programming, long
term fitness growth, program evolution, tower of
blocks, tweaking mutation behaviour learning,
behavioural sciences computing, biology computing",
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isbn13 = "978-1-4244-6910-9",
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DOI = "doi:10.1109/CEC.2010.5586375",
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abstract = "If a population of programs evolved not for a few
hundred generations but for a few hundred thousand or
more, could it generate more interesting behaviours and
tackle more complex problems? We begin to investigate
this question by introducing Tweaking Mutation
Behaviour Learning (TMBL), a form of evolutionary
computation designed to meet this challenge. Whereas
Genetic Programming (GP) typically involves creating a
large pool of initial solutions and then shuffling them
(with crossover and mutation) over relatively few
generations, TMBL focuses on the cumulative acquisition
of small adaptive mutations over many generations. In
particular, we aim to reduce limits on long term
fitness growth by encouraging tweaks: changes which
affect behaviour without ruining the existing
functionality. We use this notion to construct a
standard representation for TMBL. We then
experimentally compare TMBL against linear GP and
tree-based GP and find that TMBL shows strong signs of
being more conducive to the long term growth of
fitness.",
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DOI = "doi:10.1109/CEC.2010.5586375",
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notes = "WCCI 2010. Also known as \cite{5586375}",
- }
Genetic Programming entries for
Tony Lewis
George D Magoulas
Citations