Reasoning and Planning with Dynamically Changing Norms
📰 ArXiv cs.AI
Learn to implement norm-guided planning in AI agents that interact with humans, considering dynamically changing norms
Action Steps
- Implement a defeasible calculus to resolve normative conflicts in AI planning
- Integrate dynamically changing norms into the planning process using a human-AI setting
- Use the approach to guide planning in AI agents that interact with humans
- Test the system with various scenarios to ensure safe and norm-compliant interactions
- Refine the system based on the results of the testing and evaluation
Who Needs to Know This
AI researchers and engineers working on human-AI interaction systems can benefit from this approach to ensure safe and norm-compliant interactions
Key Insight
💡 Dynamically changing norms must be considered in AI planning to ensure safe and norm-compliant human-AI interactions
Share This
💡 Guide AI planning with dynamically changing norms to ensure safe human-AI interactions!
Key Takeaways
Learn to implement norm-guided planning in AI agents that interact with humans, considering dynamically changing norms
Full Article
Title: Reasoning and Planning with Dynamically Changing Norms
Abstract:
arXiv:2605.27622v1 Announce Type: new 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
Abstract:
arXiv:2605.27622v1 Announce Type: new 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
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