Socio-technical systems are those systems where social behaviours, that is the behaviours of groups of individuals, influence and get influenced by the physical system. Examples include how traffic distributes on a road network leading to congestions localised in space and time, or how the rejection of social restriction during the recent epidemics increased the stress on the hospitals and basic service providers. Cooperating, in these cases, corresponds to accepting a partial limitation in selfish benefits to the advantage of society. The evolution of cooperation or selfishness can be analytically described through evolutionary game theory and the literature presents several formulations for the emergence of cooperation in network structures, which represent the social interactions. However, such social interactions are mediated by the physical environment, which provides feedback for the social side. In the example of the COVID pandemic, for example, cooperation was higher where the infection levels affected the hospital activities. In those regions, people were in general more willing to use face masks and avoid social interactions. New modelling and analysis tools are hence required which can inform the mutual interaction of societal and physical dynamics. These will arise at the intersection of network and game theory.
Aim This project aims at define hybrid analytical models describing the coupled dynamics of the evolution of cooperation in dynamic environments. The hybrid nature lies in the different kinds of dynamics coexisting, which may be reconciled through a mean field approach.
● Identifying case studies where cooperation is enhanced or diminished by the system state.
● Creating multilayer network models describing the co-evolution of the cooperation and system state data.
● Generalise the model to obtain universal results on the evolution of cooperation that transcend the specific case studies.