Evolution of trust in the N-player trust game with transformation incentive mechanism

Trust game is commonly used to study the evolution of trust among unrelated individuals. It offers valuable insights into human interactions in a variety of disciplines, including economics, sociology, and psychology. Previous research has revealed that reward and punishment systems can effectively promote the evolution of trust. However, these investigations overlook the gaming environment, leaving unresolved the optimal conditions for employing distinct incentives to facilitate trust level effectively. To bridge this gap, we introduce a transformation incentive mechanism in an N-player trust game, where trustees are given different forms of incentives depending on the number of trustees in the group. Using the Markov decision process approach, our research shows that as incentives increase, the level of trust rises continuously, eventually reaching a high level of coexistence between investors and trustworthy trustees. Specifically, in the case of smaller incentives, rewarding trustworthy trustees is more effective. Conversely, with larger incentives, punishing untrustworthy trustees is of greater efficacy. Furthermore, we find that moderate incentives positively influence the average payoff within the group.

Methods
We use MATLAB to numerically compute the evolutionary dynamics of the system.