# prisoners-dilemma

the prisoner's dilemma: i have another ideabank project a "good" solution to the Prisoner's dilemma IRL is an algorithm that is X tit-for-tat and 1-X benevolent my hypothesis: 1. this is actually a pretty good approximation to real life 2. this leads to a bifurcation leading to a pecking order of groups that are more or less benevolent but finite groups a pecking order so what has been done is having different algorithms play + compete in prisoner's dilemma and they can reproduce with proliferation based on success the question is....if you adjust X, for a large sample, do you get a bifurcation? is the hypothesis valid? do you have, as observed IRL, a population that succeeds by being less benevolent by taking advantage of a population that is more benevolent?

http://www.radiolab.org/blogs/radiolab-blog/2010/dec/14/prisoners-dilemma/