If there is a third kind of player, which cooperates on the first round and then slacks thereafter, then the third group will blow the second out of the water. The second group only wins because no one bothered exploiting them in your example, even though anyone easily could have.
Sure, but then you can add a fourth kind of player, who hunts with those with reputation equal or higher than themselves, it probably beats all three others (though the outcome might depend on the initial mix, if there are more 2 than 4, 3 might exploit enough 2 to beat 4).
And then other strategies can beat that. There are plenty of "nice" strategies that are less foolish than "always slack".
TL;DR = write a python script to win this applied game theory contest for $1000. Based on Prisoner's Dilemma / Tragedy of the Commons but with a few twists. Deadline Sunday August 18.
https://brilliant.org/competitions/hunger-games/rules/
The choices are H = hunt (cooperate) and S = slack (defect), and they use confusing wording here, but as far as I can tell the payoff matrix is (in units of food)
What's interesting is you don't get the entirety of your partner's history (so strategies like Tit-Tit-Tit for Tat don't work) instead you get only their reputation, which is the fraction of times they've hunted.
To further complicate the Nash equilibria, there's the option to overhunt: a random number m, 0 < m < P(P−1) is chosen before each round (round consisting of P−1 hunts, remember) and if the total number of hunt-choices is at least m, then each player is awarded 2(P−1) food units (2 per hunt).
Your python program has to decide at the start of each round whether or not to hunt with each opponent, based on: