ﻻ يوجد ملخص باللغة العربية
Personal responsibility, one of the basic principles of modern law, requires one to be responsible for what he did. However, personal responsibility is far from the only norm ruling human interactions, especially in social and economic activities. In many collective communities such as among enterprise colleagues and family members, ones personal interests are often bound to others -- once one member breaks the rule, a group of people have to bear the punishment or sanction. Such a mechanism is termed joint liability. Although many real-world cases have demonstrated that joint liability helps to maintain collective collaboration, a deep and systematic theoretical analysis on how and when joint liability promotes cooperation is lacking. Here we use evolutionary game theory to model an interacting system with joint liability, where ones losing credit could deteriorate the reputation of the whole group. We provide the analytical condition to predict when cooperation evolves in the presence of joint liability, which is verified by simulations. We also analytically prove that joint liability can greatly promote cooperation. Our work stresses that joint liability is of great significance in promoting the current economic propensity.
Systems with simultaneous cooperation and competition among the elements are ubiquitous. In spite of their practical importance, knowledge on the evolution mechanism of this class of complex system is still very limit. In this work, by conducting ext
In this paper, we investigate the effect of heterogeneity of link weight, heterogeneity of the frequency or amount of interactions among individuals, on the evolution of cooperation. Based on an analysis of the evolutionary prisoners dilemma game on
In this study, we develop the mathematical model to understand the coupling between the spreading dynamics of infectious diseases and the mobility dynamics through urban transportation systems. We first describe the mobility dynamics of the urban pop
We describe the population-based SEIR (susceptible, exposed, infected, removed) model developed by the Irish Epidemiological Modelling Advisory Group (IEMAG), which advises the Irish government on COVID-19 responses. The model assumes a time-varying
A simplified method to compute $R_t$, the Effective Reproduction Number, is presented. The method relates the value of $R_t$ to the estimation of the doubling time performed with a local exponential fit. The condition $R_t = 1$ corresponds to a growt