The hypothesis was adding a state of aggression, territoriality in nature (patrolling food), would make them appear social.
It worked! We then transferred the learned model parameters to robots for fun (and people thought they were social). Note that we left the models an option to “evolve” in several ways, they always converted to being aggressive in defending food spawn locations.
In any case, this makes sense. When you have complex systems and you apply a sort of pressure, models (or animals) will learn to “survive” because that’s what is passed on.
EDIT: Just finished reading both and I can say the Quanta publication doesn't add anything except a short tangent about the history of self-play. Seriously, go read the openAI publication. It has great reactive visualizations and is much more put together.
It hard to get at the value of the playing Hide-and-Seek example, but it's certainly not in their anthropomorphized 'strategies'.
Stick to real games with clearly defined rules and arenas humans can also play in if you want to show progress, else it's probably made up for PR purposes.