# Reasoning and Planning with Dynamically Changing Norms

arXiv: https://arxiv.org/abs/2605.27622 · HTML: https://mlsanity.com/paper/2605.27622/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 30 references that are in the map.
- First posted on arXiv 26 May 2026.

## Builds on (most cited first, 3 of 3)

- [Beyond the Safeguards: Exploring the Security Risks of ChatGPT](https://mlsanity.com/paper/2305.08005/) (2023)
- [Learning Norms via Natural Language Teachings](https://mlsanity.com/paper/2201.10556/) (2022)
- [A Defeasible Deontic Calculus for Resolving Norm Conflicts](https://mlsanity.com/paper/2407.04869/) (2024)

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

- [Legislating World-Model-Based Planning with Legal Reasoning](https://mlsanity.com/paper/2609.15113/) (2026)

## Abstract (arXiv)

To safely interact with humans, AI agents must both know our norms and consider them during planning. However, such norm-guided planning has been less explored, only within communities of artificial agents, and has ignored the dynamic nature of norms. This paper instead presents an approach to guiding planning with dynamically changing norms in a human-AI setting. We contribute a defeasible calculus for resolving normative conflicts and an approach to using such dynamically changing norms as guard rails on plans. We theoretically demonstrate our approach with formal proofs and empirically with an AI agent, SocialBot, on a natural language dialogue task.