The book provides an investigation into how cooperation can emerge and persist as explained by the application of game theory.
TFT (and other "nice" strategies generally) "won, not by doing better than the other player, but by eliciting cooperation [and] by promoting the mutual interest rather than by exploiting the other's weakness.
Overdoing the punishment risks escalation, and can lead to an "unending echo of alternating defections" that depresses the scores of both players.
In summary, success in an evolutionary "game" correlated with the following characteristics: The lessons described above apply in environments that support cooperation, but whether cooperation is supported at all, depends crucially on the probability (called ω [omega]) that the players will meet again,[15] also called the discount parameter or, figuratively, the shadow of the future.
But in the iterated PD the value of repeated cooperative interactions can become greater than the benefit/risk of single exploitation (which is all that a strategy like TFT will tolerate).
Curiously, rationality and deliberate choice are not necessary, nor trust nor even consciousness,[16] as long as there is a pattern that benefits both players (e.g., increases fitness), and some probability of future interaction.
Often the initial mutual cooperation is not even intentional, but having "discovered" a beneficial pattern both parties respond to it by continuing the conditions that maintain it.
Other work on the evolution of cooperation has expanded to cover prosocial behavior generally,[24] and in religion,[25] other mechanisms for generating cooperation,[26] the IPD under different conditions and assumptions,[27] and the use of other games such as the Public Goods and Ultimatum games to explore deep-seated notions of fairness and fair play.
Axelrod discusses this in chapter 8; in a later paper he and Rick Riolo and Michael Cohen[31] use computer simulations to show cooperation rising among agents who have negligible chance of future encounters but can recognize similarity of an arbitrary characteristic (such as a green beard); whereas other studies[32] have shown that the only Iterated Prisoner's Dilemma strategies that resist invasion in a well-mixed evolving population are generous strategies.
When an IPD tournament introduces noise (errors or misunderstandings), TFT strategies can get trapped into a long string of retaliatory defections, thereby depressing their score.
[35] In addition to kin selection and direct reciprocity, he shows that: The payoffs in the Prisoner's Dilemma game are fixed, but in real life defectors are often punished by cooperators.
From their summary: Altruism—benefiting fellow group members at a cost to oneself —and parochialism—hostility towards individuals not of one's own ethnic, racial, or other group—are common human behaviors.
In the context of this discussion, learning rules, specifically conformism and payoff-dependent imitation, are not arbitrarily predetermined but are biologically selected.
Simulations of the model under conditions approximating those experienced by early hominids reveal that conformism can evolve even when individuals are solely faced with a cooperative dilemma, contrary to previous assertions.
These model results demonstrate robustness, maintaining validity even under conditions of high migration rates and infrequent intergroup conflicts.
[43] Neither Choi & Bowles nor Guzmán, Rodriguez-Sicket and Rowthorn claim that humans have actually evolved in this way, but that computer simulations show how war could be promoted by the interaction of these behaviors.
[44] Several software packages have been created to run prisoner's dilemma simulations and tournaments, some of which have available source code.