A minimal python code for the Robotarium (GATech) that allows reproduceable results for multi-agent robot foraging
To download the requisite files such that a python based simulation can run on your system, please head to Robotarium's Github repo at https://github.com/robotarium/robotarium_python_simulator
To submit a job in order to run the simulation based experiment on real robots, head to https://robotarium.gatech.edu NOTE: Anyone can run as many jobs (within reason) as they are free of cost.
Submit the same py file as found in this repository to reproduce a minimalist version used to collect some data for the paper: "Engineering Social Learning Mechanisms in Multi Agent Robots"
'expt1.1.py' performs 'asocial' exploration, i.e. each robot collects rewards by and for itself.
If you utilize this code for your research work, please cite the paper as follows:
O. Hamid, K. Dautenhahn and C. L. Nehaniv, "Engineering Social Learning Mechanisms for Minimalistic Multi-agent Robots," 2020 3rd International Conference on Control and Robots (ICCR), Tokyo, Japan, 2020, pp. 90-99, doi: 10.1109/ICCR51572.2020.9344158.