This is the source code for the genetic algorithm evolutionary robotics system used for the experiments in the PhD thesis "Digital control networks for virtual creatures". It can be run on a single Linux PC or a cluster (either local processing of a complete experimental run, or distributed processing of a run via a shared ZEO server).
Run time dependencies:
$ apt-get install cython python-pyode python-qt4 python-zodb
$ pip install cgkit1
Testing and graph plotting dependencies (not required for basic usage, but useful for development and analysis of experiment results):
$ apt-get install graphviz gnuplot python-cheetah texlive-font-utils
$ pip install testoob
These dependencies are for Debian Jessie. Other distributions may differ.
# Create an evolutionary run (population size 20, 10 generations)
$ ev -f test.db -p 30 -g 30 --model sigmoid --fitness walk
# Run evolution
$ ev -f test.db -m -c
# List results
$ ev -f test.db -l
Num Score P.score Mutations
0 2025.15 2011.31 0
1 1934.47 1937.14 0
|...
29 -1.00 1937.14 5
Generation: name=test.db ga=elite gen=9/9 fitness=walk evh=864
# Run simulation of result 0
$ ev -f test.db -i 0 -s
INFO:ev:Random seed: ec84baf8
INFO:ev:Running simulation
INFO:ev:Final score was 2015.727087
# Run 3D OpenGL visual simulator with result 0
$ ev -f test.db -i 0 -v
The ev command is the front end for creating GA runs, running the
simulations, creating graphs and videos, varying parameters of GA and neural
network aetc.
Run ev without any parameters to show all supported options.
Video:
Biped walker:
Cube walker:
