Norms help regulate a society. Norms may be explicit (represented in structured form) or implicit. We address the emergence of explicit norms by developing agents who provide and reason about explanations for norm violations in deciding sanctions and identifying alternative norms. These agents use a genetic algorithm to produce norms and reinforcement learning to learn the values of these norms. We find that applying explanations leads to norms that provide better cohesion and goal satisfaction for the agents. Our results are stable for societies with differing attitudes of generosity.

翻译：规范有助于规范社会,规范可以是明确(以结构化形式代表)或隐含的,规范可以是明确的(以结构化形式代表),也可以是隐含的。我们处理由发展代理人出现的明确规范的问题,这些代理人在决定制裁和确定替代规范时,对违反规范的行为提供解释并说明理由。这些代理人利用基因算法来制定规范,并加强学习学习这些规范的价值。我们发现,应用解释会导致为行为者提供更好的凝聚力和客观满意度的规范。我们的结果对于具有不同慷慨态度的社会来说是稳定的。