Is it an option to neither hunt nor slack with people with low reputation, but just avoid them?
No, each round, you have a go with each of the other remaining players.
Then this game actually seems to be about getting strategy data out of reputation data. The zeroth-level strategy is to defect very time, because that's the nash equilibrium. An example of a first-level strategy is to cooperate against players with reputation higher than some cutoff, and defect against everyone else, because you want to coooperate against cooperaters to outlast the slackers. A second level strategy models the other players modeling you, so you might for example cooperate against players with reputation higher than some function of your ...
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: