 A third mechanism by which players can be made more likely to meet those like themselves is to consider a more sophisticated dynamics of evolution that operates on groups of players as well as on the individuals within those groups. There has been a heated debate among biologists and philosophers of biology about the appropriate “units of selection” on which natural selection operates. The idea that in many cases it makes sense to take these units to be groups of individuals (instead of, or in addition to, genes or individuals) has recently been resuscitated as a respectable and plausible viewpoint. (See Sober and Wilson or Wilson and Sober for a history and impassioned defense of this resuscitation.) For cultural evolution, the idea is equally plausible—within-group behavior may be in equilibrium, but the equilibria reached by different groups may be different. Less successful groups may imitate, be replaced by, or lose members to, more successful groups. Sober and Wilson sometimes write as if evolutionary game theory is an alternative viewpoint to group selection, but it is important to understand that this is only true of simple evolutionary models like those presented above. More sophisticated evolutionary games are possible. Consider, for example, a simple version of the haystack model originally described by John Maynard Smith. Pairs of players from a large population pair randomly. Each pair colonizes a single haystack. The pair plays a prisoners dilemma and the payoffs to an individual determine the number of offspring of that individual in the next generation. (Parents die when the children are born.) For some fixed number of generations, members of the colony pair randomly with other members and play the PD. Then the haystacks are torn down, the population mixes and random pairs colonize next season's haystacks. One simple way to represent the \(n\)-generation haystack PD, as we might call it, is to view it as a game between the two initial founders of a haystack with the payoff to a founder being set to the number of living descendants who are using his strategy. (This idea is suggested in Bergstrom and reported in Skyrms 2004.) For example, suppose \(n=3\) and the temptation, reward, punishment and sucker payoffs are set to 5, 3, 1, 0. Then, if Player One cooperates and player Two defects, the payoff to Player One will be 0, because a cooperator gets 0 offspring in the second, and any subsequent, generation. The payoff to player Two will be 5 because the defector has five (like-minded) offspring among the second generation and each of these has one in the third generation since there are no cooperators left to meet. The full payoff matrix for the four generation haystack PD with payoffs 3,2,1, and 0 is given by the matrix below.