Simulations on the collective behavior of reinforcement learning agents

NOTE: This project is not finished yet. See the older version here.

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Python 3.x (preferably python 3.5)

Download or clone the repository using the big green button on the upper-right corner of the page or by using git:

git clone git://github.com/leloykun/socialsims.git

or

git clone https://github.com/leloykun/socialsims.git

Install the required libraries with pip:

pip install -r requirements.txt

or

pip3 install -r requirements.txt

You can run all of the simulations in one go with:

python main.py

The raw data for each simulation can be found in data/raw/[name of simulation]

Just run

pytest

The visuals are turned off by default to speed up the simulations.

To turn them on, simply uncomment the line with env.show() in the source code of each simulation:

# env.show()
env.show()

This is NOT recommended.

TODO: centralize this option

You can comment out the simulations in src/sims/list.txt to exclude them from being run by portal.py. For example, with the following, only simulation cat-mouse would be run with parameters 100 10 10 as [runs] [trials] [steps].

# cat-mouse [runs] [trials] [steps]
cat-mouse 10 100 10

# cat-mouse-cheese [runs] [timesteps] [interval]
# cat-mouse-cheese 10 10000 100

# simple-migration [runs] [timesteps] [temp_powers]
# simple-migration 10 10000 5

# route-choice [runs] [timesteps] [num_drivers] [[road capacities]]
# route-choice 10 1000 100 10 20 30 40

# migration [runs] [timesteps] [num_mice]
# migration 1 100000 3

TODO: fix this

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TODO move this part to 'wiki'

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TODO use seaborn facet grid to graph data

• Franz Louis Cesista
• Grade 12 student from Philippine Science High School - Eastern Visayas Campus
• Machine Learning enthusiast