In increasingly autonomous and highly distributed multi-agent systems, centralized coordination becomes impractical and raises the need for governance and enforcement mechanisms from an agent-centric perspective. In our conceptual view, sanctioning norm enforcement is part of this agent-centric approach and they aim at promoting norm compliance while preserving agents' autonomy. The few works dealing with sanctioning norm enforcement and sanctions from the agent-centric perspective present limitations regarding the representation of sanctions and the comprehensiveness of their norm enforcement process. To address these drawbacks, we propose the NPL(s), an extension of the NPL normative programming language enriched with the representation of norms and sanctions as first-class abstractions. We also propose a BDI normative agent architecture embedding an engine for processing the NPL(s) language and a set of capabilities for approaching more comprehensively the sanctioning norm enforcement process. We apply our contributions in a case study for improving the robustness of agents' decision-making in a production automation system.

翻译：在日益自主且高度分布的多智能体系统中，集中式协调变得不切实际，从而需要从智能体中心视角建立治理与执行机制。在我们的概念框架中，制裁型规范执行是这种智能体中心方法的一部分，其目标是在维护智能体自主性的同时促进规范遵从。现有少数从智能体中心视角探讨制裁型规范执行与制裁的研究，在制裁的表示及其规范执行过程的全面性方面存在局限。为解决这些缺陷，我们提出NPL(s)——一种NPL规范编程语言的扩展，该扩展将规范与制裁作为一等抽象加以表示。我们还提出一种BDI规范智能体架构，内置用于处理NPL(s)语言的引擎以及一组能力，以更全面地处理制裁型规范执行过程。我们通过一个案例研究来应用上述贡献，以提升生产自动化系统中智能体决策的鲁棒性。