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Linear Genetic Programming in Python Bytecode
--client
pyconau
--show
pycon_au_2016
--room Room_104 11325 --force
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Author(s):
Mark Burgess
Location
Room 104
Date
aug Sat 13
Days Raw Files
Start
11:50
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Duration
0:30:00
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None
End
12:20
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None min.
https://2016.pycon-au.org/schedule/99/view_talk
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A quick tutorial on genetic programming and its implementation in Python. Including the general process of evolution, the various representations of programs and particularly linear genetic programming. Some really basic python libraries are introduced, including the DEAP and pyevolve frameworks. It has been presented and prototyped by github user mgard (and documented http://multigrad.blogspot.com.au/2014/06/fun-with-python-bytecode.html) that python bytecode itself could be directly evolved in linear genetic programming to alleviate the overhead of compiling the permutations of trees generated by the evolutionary process. Python bytecode itself is redly accessed and created by Cpython, though not compatible between versions and a subset of python bytecode instructions will be selected for the implementation of a basic example of symbolic regression. A futher and more useful example will be provided.
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