User:Wonhol
From Robin
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** https://gist.github.com/stefanopalmieri This guy has some nice examples binding multineat and gym env | ** https://gist.github.com/stefanopalmieri This guy has some nice examples binding multineat and gym env | ||
** installation | ** installation | ||
- | *** install boost | + | *** install boost, first bootstrap with python version 3.6 then build |
- | *** | + | *** git clone multineat then |
- | + | $ export MN_BUILD=boost | |
- | + | $ python3 setup.py build_ext | |
- | + | $ python3 setup.py install | |
- | *** | + | *** in case it casts missing library link to python and numpy, make sure to install boost with python specified |
- | + | and numpy is installed properly for the user | |
- | + | *** once installed, test by | |
- | + | >>> import MultiNEAT | |
- | + | *** in case it casts missing library error, explicitly set $LD_LIBRARY_PATH for boost install location, by default | |
- | + | $ export LD_LIBRARY_PATH=/usr/local/lib | |
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=== Week 36 === | === Week 36 === |
Revision as of 08:36, 9 September 2019
Contents |
Goals
We are taking the start point from the paper from Risi,
Risi - Evolving flexible controller for locomotion
where locomotive controller for variable length legges were evolved with HyperNEAT approach.
The goal is to implement it on DyRet platform - where it has two actuator for each legges. Also other thing to consider will be taking account of Tegotae - where touch input is used as some kind of feedback to CPG. Risi had touch sensor as input to his substrate in the simulation.
Other aspect of it is to see if HyperNEAT approach is something plausible considering its complexity - some skeptical veiw on HyperNEAT. ie) simple CTRNN network with length of leg as one of the input.
Some of the tasks that could be done over the summer are
* Read through DyRet doucumentation from robin wiki & github and set up a simulator enviorment * Theoretical understanding of Tegotae - is it plausible to embed it with CTRNN-substrate? * Experimenting with HyperNEAT libraries - Kyrre`s recommendation is "C++/Python MultiNEAT C++ with Python binding", otherwise Risi seems to
work with C# implementation -> perhaps it is a good idea to have a look.
OpenAI Gym Env for DyRET
https://github.uio.no/jorgehn/gym-dyret
HyperNEAT libraries
TODO
Plan for Fall semester
2019 September October November December Su 1 8 15 22 29 6 13 20 27 3 10 17 24 1 8 15 22 29 Mo 2 9 16 23 30 7 14 21 28 4 11 18 25 2 9 16 23 30 Tu 3 10 17 24 1 8 15 22 29 5 12 19 26 3 10 17 24 31 We 4 11 18 25 2 9 16 23 30 6 13 20 27 4 11 18 25 Th 5 12 19 26 3 10 17 24 31 7 14 21 28 5 12 19 26 Fr 6 13 20 27 4 11 18 25 1 8 15 22 29 6 13 20 27 Sa 7 14 21 28 5 12 19 26 2 9 16 23 30 7 14 21 28 35 36 37 38 39 39 40 41 42 43 43 44 45 46 47 48 49 50 51 52
Remarks
Delivery in May 2020 Mid-term presentation in week 49
Week 35
OpenAI gym setup for DyRET
Get used to DyRET Env
- input param for step : 12 np vector for joints, 8 for extension
HyperNEAT libraries
Lists of some promising ones
- https://github.com/ukuleleplayer/pureples
- Pure python-based HyperNEAT, ES-HyperNEAT library, based on neat-python library
- Installed and provided example experiments runs fine
- https://github.com/peter-ch/MultiNEAT
- MultiNEAT, implemented in C++ with python bindings
- good review from Stanley's website
- https://gist.github.com/stefanopalmieri This guy has some nice examples binding multineat and gym env
- installation
- install boost, first bootstrap with python version 3.6 then build
- git clone multineat then
$ export MN_BUILD=boost $ python3 setup.py build_ext $ python3 setup.py install
- in case it casts missing library link to python and numpy, make sure to install boost with python specified
and numpy is installed properly for the user
- once installed, test by
>>> import MultiNEAT
- in case it casts missing library error, explicitly set $LD_LIBRARY_PATH for boost install location, by default
$ export LD_LIBRARY_PATH=/usr/local/lib
Week 36
OpenAI gym setup HyperNEAT library test
by this point, familir with hyperNEAT packages and chosen one for the project OpenAI gym env setup for various experiments
Week 37
Experiment setup Implementing Risi's HyperNEAT on Dyret
Week 38
Experiment setup Implementing Risi's HyperNEAT on Dyret
Week 39
Experiment setup Implementing Risi's HyperNEAT on Dyret
Week 40
Experiment setup Implementing CPG style locomotive controller on Dyret
Week 41
Experiment setup Implementing CPG style locomotive controller on Dyret
Week 42
Experiment setup Implementing CPG style locomotive controller on Dyret
Week 43
Experiment run
Week 44
Experiment run
Week 45
Experiment run
Week 46
Experiment analysis
Week 47
Experiment analysis
Week 48
Experiment analysis
Week 49
Presenting first results