Ubi Lex, Ibi Poena: Designing Norm Enforcement in E-Institutions
Coordination, Organizations, Institutions, and Norms in Agent Systems II
Norm internalization in artificial societies
AI Communications - European Workshop on Multi-Agent Systems (EUMAS) 2009
Distributed punishment as a norm-signalling tool
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
Generating norm-related emotions in virtual agents
IVA'12 Proceedings of the 12th international conference on Intelligent Virtual Agents
Robust Regulation Adaptation in Multi-Agent Systems
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Social norms for self-policing multi-agent systems and virtual societies (extended abstract)
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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As explained by Axelrod in his seminal work An Evolutionary Approach to Norms, punishment is a key mechanism to achieve the necessary social control and to impose social norms in a self-regulated society. In this paper, we distinguish between two enforcing mechanisms. i.e. punishment and sanction, focusing on the specific ways in which they favor 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 simulation show us that sanction is more effective and less costly than punishment in the achievement and maintenance of cooperation and it makes the population more resilient to sudden changes than if it were enforced only by mere punishment.