# Deontic Paradoxes in ASP with Weak Constraints

arXiv: https://arxiv.org/abs/2308.15870 · HTML: https://mlsanity.com/paper/2308.15870/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 26 references that are in the map.
- First posted on arXiv 30 Aug 2023.

## Builds on (most cited first, 1 of 1)

- [Safe Reinforcement Learning via Shielding](https://mlsanity.com/paper/1708.08611/) (2017)

## Built on by (most cited first, 1 of 1)

- [Modeling Deontic Modal Logic in ASP](https://mlsanity.com/paper/2507.05519/) (2025)

## Abstract (arXiv)

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.