Emergent behaviours in multi-agent systems with Evolutionary Game Theory

The mechanisms of emergence and evolution collective behaviours in dynamical Multi-Agent Systems (MAS) multiple interacting agents, with diverse behavioral strategies co-presence, have been undergoing mathematical study via Evolutionary Game Theory (EGT). Their systematic also resorts to agent-based modelling simulation (ABM) techniques, thus enabling the aforesaid under a variety conditions, parameters, alternative virtual games. This paper summarises some main research directions challenges tackled our group, using methods from EGT ABM. These range introduction cognitive emotional into agents’ implementation an evolving MAS, cost-efficient interference for promoting prosocial complex networks, regulation governance AI safety development ecology, equilibrium analysis random evolutionary multi-player brief aims sensitize reader based issues, results prospects, which are accruing importance modeling minds machines engineering impact on understanding stability behaviours. In all cases, important open problems MAS as viewed or prioritised by group described.