Aging effects in Coordination games
Ciardella, Samuele (supervisors: San Miguel, Maxi; Galla, Tobias)
Master Thesis (2023)
Social science studies often use evolutionary coordination games to model how consensus is reached. These models simulate how agents choose and change their strategies. However, models applied until now to coordination games do not account for the attachment an agent may develop to their current state, and how the time spent following a certain strategy can make change more difficult. This is where the concept of aging comes into play.
Aging is defined as resistance to change due to time spent in a particular state. In other words, the longer an agent has been following a certain strategy, the more difficult it becomes for them to change. This can be thought of as the “inertia” of people sticking with their own ideas.
In this study, we analyze the effect of aging on an evolutionary coordination game. We repeat the analysis for two network types, random regular and fully connected network, to examine the effect of structure on the results. Our objective is to introduce the concept of “inertia” into the coordination game and to determine if coordination is still possible despite this resistance to change. By incorporating the concept of aging into our model, we are trying to more accurately represent real-world scenarios and better understand how consensus is reached within a system.
Our research indicates that the process of aging does affect the coordination within a system. When we contrast a network where aging is a factor with one where it is not, we observe that the presence of aging prolongs the duration required to achieve consensus.
In conclusion, this study provides valuable insights into the role of aging and network structure in coordination games: aging process, which reduces the likelihood of a node changing its state, can decelerate or even stop the coordination process. Meanwhile, the structure of the network can influence both the speed and behavior of the decay.
By accounting for these factors, we can improve our understanding of how consensus is reached within a system and develop more effective strategies for achieving coordination.