All useful information about the ARGoS3-AutoMoDe-rvr package, including installation and utilization instructions, are regrouped in the following technical report (techrep). Please cite this report if you use the ARGoS3-AutoMoDe-rvr package.
bin
This empty folder will contain the executable automode_main after compilation.experiments
The folder where all experiments configuration files (.argos or .xml) are locatedchocolate
The experiment configuration files of the experiments described in chocolateexample
The experiment configuration file used as example in the technical report of the package.
optimization
The folder where one should place files regarding the optimization algorithm used (including grammar generator for the irace algorithm)example
The necessary elements to launch irace on a small example described in the technical report.
src
The source files of ARGoS3-AutoMoDe package.cmake
The .cmake files for ARGoS3.core
The core classes of ARGoS3-AutoMoDe-rvr.modules
The behaviors and conditions modules described in chocolate
AutoMoDeMain.cpp
:: The main procedure to launch ARGoS3-AutoMoDe-rvr.
- ARGoS3 (3.0.0-beta48)
- argos3-rvr
- rvr-loop-functions (master)
- demiurge-rvr-dao (master)
$ git clone https://github.com/demiurge-project/ARGoS3-AutoMoDe-rvr.git
$ cd argos3-AutoMoDe-rvr
$ mkdir build
$ cmake ..
$ make
Once compiled, the bin/
folder should contain the automode_main
executable.
To run a single experiment, you need to use the automode_main
as follows:
usage: automode_main [-r | --readable] [-c | --config-file configfile] [-m | --method method] [-s | --seed seed] [--fsm-config fsmconfig]
options:
[-c | --config-file configfile] Path to the .argos|.xml experiment file to use [REQUIRED]
[-r | --readable] Prints an URL containing a DOT representation of the finite state machine [OPTIONAL]
[-s | --seed seed] The random seed for the ARGoS3 simulator [OPTIONAL]
[--fsm-config fsmconfig] the description of the finite state machine in the AutoMoDe format [REQUIRED]
To run the design process you will need the
irace
package and a
fonctional R
distribution.
If you are using an MPI capable computing cluster you can use the
parallel-irace-mpi
located in the optimization/
folder.
Otherwise, you can directly launch irace with the command:
irace --exec-dir=EXECDIR --seed SEED --scenario scenario
options:
[--exec-dir=execdir] the execution folder
[--seed seed] the random seed for the optimization algorithm
[--scenario scenario] the scenario file of the experiment
For example (in the optimization/
folder):
irace --exec-dir=aggregation --seed 1234 --scenario scenario.txt
This will run the optimization algorithm for 200k simulation in order to train for the aggregation mission (see chocolate for details on missions).
- [techrep] Kegeleirs, M., Todesco, R., Garzon Ramos, D., Legarda Herranz, G., Birattari, M. (2022).Mercator: hardware and software architecture for experiments in swarm SLAM. Technical report TR/IRIDIA/2022-012, IRIDIA, Université libre de Bruxelles, Belgium.
- [chocolate] Francesca, G., Brambilla, M., Brutschy, A., Garattoni, L., Miletitch, R., Podevijn, G., ... & Mascia, F. (2015). AutoMoDe-Chocolate: automatic design of control software for robot swarms. Swarm Intelligence, 9(2-3), 125-152.