Effects of reward distribution strategies and perseverance profiles on agent-based coalitions dynamics

In a conventional political system, leaders decide how to distribute benefits to the population and coalitions can emerge when other individuals support the candidates. This work intends to analyze how different leader strategies and individual profiles affect the way coalitions are formed and rewards are shared. Using agent-based simulation, we simulated a model in which individuals of three different perseverance profiles (patient, intermediate and impatient) eventually decide to be part of coalitions by supporting certain leaders when aiming to maximize their own earnings. Leaders can follow one of three different strategies to share rewards: altruistic, intermediate and egoistic. The results show that egoistic leaders stimulate the competition for rewards and the formation of coalitions, causing greater inequalities, while impatient individuals also promote more instability and lead to a higher concentration of rewards.