  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.
