Population Behaviours

Backstory

university pair coursework. The task was quite open ended, thus interesting: “Draw some interesting conclusion from the use of NetLogo and tweaking of available variables”. So I decided to resort to my all time favourite topic, i.e. altruism vs selfish behaviours. My course mate was happy because he didn’t care much about that, he was more interested in getting consistent results, which in hindsight it turned out to be a useful matching of preferences.

Geeky Stuff

What we could control was the behaviour of 2 populations and laws of the environment they coexist in (lifespan, conditions for replication, preferred food sources, etc...).
The cool thing about NetLogo is that you can specify these rules and click run and a simulation of your fine-tuned world appears before your eyes (fascinating, especially for me, the guy who tried to actually do this before knowing that this was already a thing ). On top of all this, NetLogo allows you to create live graphs recording any possible parameter that you specify in the code. Looking at this project’s video, the main graph we’re interested in is the top right one which records the number of altruists (green) and selfish individuals (red) in the simulation.

How you can run this

How to use the program

Once all is loaded on https://www.netlogoweb.org/, just press the "setup" button and then the "go" button

Thoughts

What becomes apparent from this graph is the conclusion we ended up describing in the coursework report. With set environment variables, cooperation is vital for fast development of a population; after a successful growth, selfish individuals will take over. Kind of sad, but true if you think about it.
Imagine someone in the Stone Age trying to “make it” on his own. Not a chance. Imagine someone making it on its own in our times. People can survive now without necessarily collaborating and being altruistic.
So going back to our hypothesis, it helped that it kind of made sense in the real world as well as in the digital world. This is why these simulations are so interesting if done right. They can give out cues and inspiration for real world applications.

Acknowledgements
  1. Smaldino PE (2013) Cooperation in harsh environments and the emergence of spatial patterns. Chaos, Solitons, and Fractals 56: 6-12.
  2. Smaldino PE, Schank JC, McElreath R (2013) Increased costs of cooperation help cooperators in the long run. American Naturalist 181: 451-463.