README:

This is a guide to executing the code of the Kitchen model which simulates a group of students attempting to keep their shared kitchen clean.
The model consists of two core files, one exectuing file and two analysis files:
	agent.py (agents file)
	model.py (model file)
	kitchen_pd.py (execution file)
	Sensitivity.py (module analysis)
	parameters.py (parameter analysis)

Required python libraries:
	-Mesa https://docs.mesastar.org/en/latest/installation.html
	-Numpy https://numpy.org/install/
	-Matplotlib https://matplotlib.org/stable/users/installing/index.html
	-random https://pypi.org/project/random2/

running the code:
	You run the code by executing python kitchen_pd.py in the command line

	If you wish to eddit the model you can open the kitchen_pd.py file and change the parameters and active modules in the line:
	model_base = Kitchen(cf =0, cleaning_mode = "proportional",  sp_mode="mode1", remove_player = True, learning_mode = True, variable_rows = 21)

	cf (int between -10 and 10): initial cleanliness factor
	cleaningmode (str): 'proportional' for the proportional cleaning method where each agent cleans only a little or 'full' where one agent can clean the entire kitchen
	n_agents (int > 1): an integer that is larger than or equal to 2 for the number of agents.
	sp_mode (str): 'none' for no social punishment aspect or 'mode1' for a model which punishses agents for not cleaning
	remove_player(Boolean): Remove agents if they deffect to much if set to True
	learning_mode(Boolean): If true the agents will look at past outcomes of decissions and change their strategy based on that
	Variables rows (int > 3 and odd): An integer that determines how many steps should be looked at when learning from past decissions, should be an odd integer and at least 3.