Reasoning and Planning with Dynamically Changing Norms

2026-05-26

AI Summary

Existing AI planning approaches struggle to effectively model dynamic and potentially conflicting social norms, limiting their ability to generate norm-compliant behaviors in human–AI interaction. This work proposes a novel method that integrates defeasible reasoning with norm-guided planning, embedding dynamic social norms as retractable constraints within the planning process to enable real-time, norm-aware decision-making. The approach synergistically combines defeasible logical inference, norm-driven planning, and formal verification, and is implemented within a natural language dialogue system. Theoretical analysis establishes its correctness, while experiments with SocialBot demonstrate that the AI can generate responses that are both contextually appropriate and compliant with evolving social norms—marking the first realization of real-time adherence to and resolution of conflicts among dynamic social norms in human–AI interaction.

Abstract

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.

Problem

• norm-guided planning
• dynamically changing norms
• human-AI interaction
• normative conflicts
• AI planning

Innovation

• dynamic norms
• defeasible calculus
• norm-guided planning
• human-AI interaction
• plan guard rails