Cooperative Cuisine Environment

The overcooked-like cooperative cuisine environment for real-time human cooperative interactions and artificial agents.

For an extensive introduction, have a look at the Documentation.

Installation

You have two options to install the environment. Either clone it and install it locally or install it in your site-packages. You need a Python 3.10 or newer environment conda environment.

Local Editable Installation

In your repo, PyCharmProjects or similar directory with the correct environment active:

conda install -c conda-forge pygraphviz
git clone https://gitlab.ub.uni-bielefeld.de/scs/cocosy/cooperative-cuisine.git
cd cooperative-cuisine
pip install -e .

Run

Run it via the command line (in your pyenv/conda environment):

cooperative-cuisine start -s localhost -sp 8080 -g localhost -gp 8000

The arguments shown are the defaults.

You can also start the Game Serverm Study Server (Matchmaking),and the PyGame GUI individually in different terminals.

cooperative-cuisine game-server -g localhost -gp 8000 --manager-ids SECRETKEY1 SECRETKEY2

cooperative-cuisine study-server -s localhost -sp 8080 -g localhost -gp 8000 --manager-ids SECRETKEY1

cooperative-cuisine gui -s localhost -sp 8080 -g localhost -gp 8000

You can start also several GUIs. The study server does the matchmaking.

Library Installation

The correct environment needs to be active:

pip install cooperative_cuisine@git+https://gitlab.ub.uni-bielefeld.de/scs/cocosy/cooperative-cuisine@main

Run

You can now use the environment and/or simulator in your python code. Just by importing it import cooperative_cuisine

Configuration

The environment configuration is currently done with 3 config files + GUI configuration.

Item Config

The item config defines which ingredients, cooking equipment and meals can exist and how meals and processed ingredients can be cooked/created.

Layout Config

You can define the layout of the kitchen via a layout file. The position of counters are based on a grid system, even when the players do not move grid steps but continuous steps. Each character defines a different type of counter. Which character is mapped to which counter is defined in the Environment config.

Environment Config

The environment config defines how a level/environment is defined. Here, the available plates, meals, order and player configuration is done.

Study Config

When starting a study, the study config holds all the information about the levels (layouts, dishes, orders). In the argument_parser.py it can be chosen whether the orders should in appear in a random ordering or whether their schedule should be pre-defined.

PyGame Visualization Config

Here the visualisation for all objects is defined. Reference the images or define a list of base shapes that represent the counters, ingredients, meals and players.

Troubleshooting

cannot open shared object file: No such file or directory (search paths /usr/lib/x86_64-linux-gnu/dri:\$${ORIGIN}/dri:/usr/lib/dri, suffix _dri) if you have a conda environment:

conda install -c conda-forge libstdcxx-ng

License

Cooperative Cuisine © 2024 by Social Cognitive Systems Group is licensed under CC BY-NC-SA 4.0