Clone this repo:

https://github.com/divilian/IPD-LLM

and run the program as follows (for instance):

$ python cli.py 150 \
    --agent-fracs TFT 0.3 Mean 0.3 Sucker 0.4 \
    --p-same 0.1 --p-diff 0.01 \
    --num-iter 100 --plot

You can run “python cli.py -h“, too, to see all the command line arguments and what they mean.

Bonus points to anyone who can vary the parameters such that (1) they maintain at least 5% of all three non-LLM agent types (Mean, Sucker, and TFT), and (2) the tit-for-tat agents, on average, come out the winners.