Within the area of multi-agent systems, normative systems are a widely used framework for the coordination of interdependent activities. A crucial problem associated with normative systems is that of synthesising norms that will effectively accomplish a coordination task and that the agents will comply with. Many works in the literature focus on the on-line synthesis of a single, evolutionarily stable norm (convention) whose compliance forms a rational choice for the agents and that effectively coordinates them in one particular coordination situation that needs to be identified and modelled as a game in advance. In this work, we introduce a framework for the automatic off-line synthesis of evolutionarily stable normative systems that coordinate the agents in multiple interdependent coordination situations that cannot be easily identified in advance nor resolved separately. Our framework roots in evolutionary game theory. It considers multi-agent systems in which the potential conflict situations can be automatically enumerated by employing MAS simulations along with basic domain information. Our framework simulates an evolutionary process whereby successful norms prosper and spread within the agent population, while unsuccessful norms are discarded. The outputs of such a natural selection process are sets of codependent norms that, together, effectively coordinate the agents in multiple interdependent situations and are evolutionarily stable. We empirically show the effectiveness of our approach through empirical evaluation in a simulated traffic domain.

中文翻译：

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演化稳定的规范系统的离线综合。

在多主体系统领域，规范系统是协调相互依存活动的广泛使用的框架。与规范系统相关的一个关键问题是综合将有效完成协调任务并且代理将遵守的规范。文献中的许多著作都集中于一个单一的，进化上稳定的规范（惯例）的在线综合，该规范的顺从性形成了代理商的合理选择，并在一种特定的协调情况下有效地协调了代理商，这些情况需要被识别和建模为一个代理。提前比赛。在这项工作中，我们介绍了一个用于演化稳定规范​​系统的自动离线综合的框架。在无法相互事先确定或单独解决的多个相互依赖的协调情况下协调代理。我们的框架源于进化博弈论。它考虑了多主体系统，其中可以通过采用MAS模拟以及基本域信息来自动枚举潜在冲突情况。我们的框架模拟了一个演化过程，在此过程中，成功的规范在代理主体中得以繁荣和传播，而不成功的规范则被丢弃。这种自然选择过程的输出是一组相互依赖的规范共同有效地协调了多个相互依存情况下的特工，并且在进化上是稳定的。我们通过在模拟交通领域中的经验评估，以经验方式展示了我们方法的有效性。