# Constraining World-Model Planning with Legal Reasoning: Validation of a Defeasible Deontic Logic Planning Stack on a Simulated Robotic Arm

- Source: arXiv cs.RO
- Published: 2026-10-28T04:00:00.000Z
- RoboHot: https://robohot.news/en/items/gb4293wdgafoayae5zl21q66x
- Original: https://arxiv.org/abs/2609.15113

## Summary

The paper proposes a legal planning stack that uses Defeasible Deontic Logic (DDL) to constrain a motion planner, leveraging a learned world model for planning and to supply legal context, thereby enabling ex ante intervention before an illegal action is executed. The stack was deployed in a scenario where a simulated robotic arm pushes blocks on a 3x3 grid. Results show that the legally constrained agent complied with norms at a markedly higher rate than the unconstrained one, and that modeling perceptual uncertainty further raised the compliance rate; legal reasoning ran efficiently at runtime, its rulings were auditable, and the stack adapted to exogenous signals and endogenous rule changes.