The rise of powerful AI technology for a range of applications that are
sensitive to legal, social, and ethical norms demands decision-making support
in presence of norms and regulations. Normative reasoning is the realm of
deontic logics, that are challenged by well-known benchmark problems (deontic
paradoxes), and lack efficient computational tools. In this paper, we use
Answer Set Programming (ASP) for addressing these shortcomings and showcase how
to encode and resolve several well-known deontic paradoxes utilizing weak
constraints. By abstracting and generalizing this encoding, we present a
methodology for translating normative systems in ASP with weak constraints.
This methodology is applied to "ethical" versions of Pac-man, where we obtain a
comparable performance with related works, but ethically preferable results.

AI 技术的崛起在面对法律、社会和伦理规范敏感的各种应用中需要决策支持，而规范推理是德意志逻辑的领域，在解决著名的基准问题（德意志悖论）方面存在挑战，并且缺乏高效的计算工具。本文使用 Answer Set Programming (ASP) 来解决这些不足，并展示了如何利用弱约束编码和解决几个著名的德意志悖论。通过抽象和概括这种编码，我们提出了一种将 ASP 与弱约束组合的方法论来翻译规范系统的方法。该方法应用于 “道德” 版本的 Pac-man 游戏中，我们得到了与相关作品相当的性能，但是结果更加符合伦理要求。