Partner switching promotes cooperation among myopic agents on a geographical plane

Interpersonal trust: Asymptotic analysis of a stochastic coordination game with multi-agent learning

We study the interpersonal trust of a population of agents, asking whether chance may decide if a population ends up with high trust or low trust. We model this by a discrete time, stochastic coordination game with pairwise interactions occurring at random in a finite population. Agents learn about the behavior of the population using a weighted average of what they have observed in past interactions. This learning rule, called an "exponential moving average," has one parameter that determines the weight of the most recent observation and may, thus, be interpreted as the agent's memory. We prove analytically that in the long run, the whole population always either trusts or doubts with the probability one. This remains true when the expectation of the dynamics would indicate otherwise. By simulation, we study the impact of the distribution of the payoff matrix and of the memory of the agents. We find that as the agent memory increases (i.e., the most recent observation weighs less), the actual dynamics increasingly resemble the expectation of the process. We conclude that it is possible that a population may converge upon high or low trust between its citizens simply by chance, though the game parameters (context of the society) may be quite telling.

Costs for switching partners reduce network dynamics but not cooperative behaviour

Social networks represent the structuring of interactions between group members. Above all, many interactions are profoundly cooperative in humans and other animals. In accordance with this natural observation, theoretical work demonstrates that certain network structures favour the evolution of cooperation. Yet, recent experimental evidence suggests that static networks do not enhance cooperative behaviour in humans. By contrast, dynamic networks do foster cooperation. However, costs associated with dynamism such as time or resource investments in finding and establishing new partnerships have been neglected so far. Here, we show that human participants are much less likely to break links when costs arise for building new links. Especially, when costs were high, the network was nearly static. Surprisingly, cooperation levels in Prisoner's Dilemma games were not affected by reduced dynamism in social networks. We conclude that the mere potential to quit collaborations is sufficient in humans to reach high levels of cooperative behaviour. Effects of self-structuring processes or assortment on the network played a minor role: participants simply adjusted their cooperative behaviour in response to the threats of losing a partner or of being expelled.

The evolution of reputation-based partner-switching behaviors with a cost

Humans constantly adjust their social relationships and choose new partners of good reputations, thereby promoting the evolution of cooperation. Individuals have to pay a cost to build a reputation, obtain others' information and then make partnership adjustments, yet the conditions under which such costly behaviors are able to evolve remain to be explored. In this model, I assume that individuals have to pay a cost to adjust their partnerships. Furthermore, whether an individual can adjust his partnership based on reputation is determined by his strategic preference, which is updated via coevolution. Using the metaphor of a public goods game where the collective benefit is shared among all members of a group, the coupling dynamics of cooperation and partnership adjustment were numerically simulated. Partner-switching behavior cannot evolve in a public goods game with a low amplification factor. However, such an effect can be exempted by raising the productivity of public goods or the frequency of partnership adjustment. Moreover, costly partner-switching behavior is remarkably promoted by the condition that the mechanism of reputation evaluation considers its prosociality. A mechanism of reputation evaluation that praises both cooperative and partner-switching behaviors allows them to coevolve.