Dynamic Sanctioning for Robust and Cost-Efficient Norm Compliance

As explained by Axelrod in his seminal work An Evolutionary Approach to Norms , punishment is a key mechanism to achieve the necessary social con- trol and to impose social norms in a self-regulated society. In this paper, we distinguish between two enforcing mechanisms. i.e. punishment and sanc- tion , focusing on the specific ways in which they fa- vor the emergence and maintenance of cooperation. The key research question is to find more stable and cheaper mechanisms for norm compliance in hybrid social environments (populated by humans and computational agents). To achieve this task, we have developed a normative agent able to punish and sanction defectors and to dynamically choose the right amount of punishment and sanction to impose on them ( Dynamic Adaptation Heuristic ). The results obtained through agent-based simula- tion show us that sanction is more effective and less costly than punishment in the achievement and maintenance of cooperation and it makes the pop- ulation more resilient to sudden changes than if it were enforced only by mere pu