Nearly all major conflicts across the globe, both current and historical, are characterized by individuals defining themselves and others in terms of their group membership. Substantial empirical evidence supports people’s tendency to favor in-group members and show hostility towards out-group individuals1,2,3,4,5. From an evolutionary perspective, numerous studies have shown how in populations comprised of various groups, group-biased behavior that discriminates or is hostile against out-groups evolves or emerges readily and dominantly6,7,8,9,10,11,12. Since humans are social beings who establish and define groups constantly, the development of out-group hostility and resulting group conflict might thus seem inevitable.

In a puzzling contrast, statistics have shown that violence and out-group conflict have actually declined dramatically over the past few centuries of human civilization, suggesting out-group hostility is not inevitable after all13,14. What factors might lead to such a decrease in conflict? Evolutionary game-theoretic models can shed light on this question by exploring how various factors affect the emergence and maintenance of individuals’ behaviors relating to group conflict.

Our evolutionary game model builds on a prior model developed in Hammond and Axelrod’s pioneering work6 on the evolution of ethnocentrism and used, for example, in Hartshorn, et al.12. In their model, agents had perceivable group tags, played one-shot Prisoner’s Dilemma games with their neighbors and could behave differently toward in-group members than out-group members. Each agent’s inherited traits included a group tag, an action (cooperate or defect) to use with in-group members and a similar action to use with out-group members. Thus there were four possible strategies: Cooperate with both in-group and out-group members; Defect against both in-group and out-group members; Ethnocentric (cooperate with in-group members, defect against out-group members); Traitorous (defect against in-group members, cooperate with out-group members).

Using their model with four different groups (or group tags), we have replicated their result showing that after a period in which Cooperative agents are briefly abundant, evolutionary pressure leads to a predominance of Ethnocentric agents. Defectors and Traitors never establish themselves (see the Supplementary Material for details).

Since the agents in that model conditioned their actions only on the group tags, they were in effect group-entitative. That leaves open the question whether there are conditions under which individual-entitative agents—agents that base their actions on knowledge of individuals per se rather than group tags—may be able to exist and perhaps even be favored by evolutionary pressures.

Moreover, that model does not incorporate mobility. Research in cultural psychology has demonstrated large empirical differences in residential mobility around the globe with important psychological consequences15,16. Researchers have shown that in high-mobility contexts, individuals change relationships often; they form new relationships and sever unwanted relationships with great ease17,18. In such contexts, having a broad network of weak ties and being open toward strangers (with whom it might be valuable to form relationships) is highly adaptive. Indeed, Oishi, et al.18 observe that in highly mobile contexts, “since it is hard to keep track of behaviors of many strangers whom one meets, one needs to carefully avoid being associated with defectors or free-riders in order to exploit the greatest possible relational benefit” (p. 228). Thus, individuals are more likely to adopt strategies that try to evaluate the “trustworthiness and worth”18 of others in highly mobile contexts, i.e., adopt individual-entitative strategies. On the other hand, in low-mobility contexts, individuals have far fewer opportunities to form new relationships and severing existing relationships can have extreme adverse effects such as being ostracized from one’s only social circle18, causing “the existential, social and psychological death of the individual” (p. 755)19. Based on these theories we would predict that group-entitative behavior and associative ethnocentrism is adaptive in low mobility societies, yet it is maladaptive in high-mobility contexts, where individual-entitative strategies would be evolutionarily favored.

We have run extensive new evolutionary simulations, augmenting the prior model to include individual-entitative strategies and mobility; and our results show that the evolution of ethnocentrism is driven by low mobility. Indeed, our subsequent empirical analysis of archival data verifies that contexts with high residential mobility have less out-group hostility than those with low mobility.

In our evolutionary game model, agents are arranged on a toroidal (wrap-around) grid, so that every node on the grid is connected to 4 neighboring nodes). Initially the grid is empty. The sequence of events at each time step is shown in Fig. 1; these are the same as in Hammond and Axelrod’s paper6 except for the Mobility stage, which is new. For additional details, see the Methods section.

Figure 1 Sequence of events at each time step in our evolutionary game-theoretic model. The sequence of steps are the same as in Hammond and Axelrod’s paper6 except for the Mobility stage, which is new. For additional details, see the Methods section. Full size image

The agents’ strategies are similar to those in Hammond and Axelrod’s model6, where agents can distinguish between in-group and out-group members by observing the group tags. Hence agents’ strategies can be conditioned on whether they are interacting with in-group or out-group members. In addition, in our model, each agent’s strategies can be conditioned on the past history of other agents. Each agent can either be group-entitative or individual-entitative and this is an inherited trait.

A group-entitative agent i ignores individual identities. Its actions toward an agent j depend only on its last encounter with anyone in j’s group. It has two possibly different strategies: one for in-groups and another for out-groups. Each of those strategies is one of the following: AllC (always cooperate), AllD (always defect), TFT (Tit-for-Tat: play whatever action the opponent played in i’s last interaction with anyone from j’s group), or OTFT (play the opposite of what TFT would play). For details about i’s behavior during its first encounter with each group, see the Supplementary Material.

An individual-entitative agent i ignores other agents’ group tags; i’s action toward j depends only on its last encounter specifically with j. Thus i has one of the above four strategies, except that TFT and OTFT depend on i’s last interaction with j specifically, rather than someone in j’s group.

To model mobility, there is a probability m with which, at the beginning of each iteration, an agent moves to a randomly chosen empty spot in the network. Thus a high value of m represents a highly mobile population, while a low value of m represents a population with low mobility. We vary m from 0 to 0.08 in our experiments. It is important to note that a mobility probability of 0.08 is quite high: it means that on average, 8% of the population move to different locations on each iteration—a substantial amount of movement even for small values of m. At higher levels of mobility (m > 0.1), cooperation breaks down in a society and the majority of the population starts defecting—and thus is not representative of any stable society around the world (see the Supplementary Material for details).