Operationalising Normative Rules in Autonomous Robotic Systems through Context-Oriented Programming

Abstract

The growing sensitivity to human aspects in autonomous systems engineering calls for principled approaches to embed ethical and normative concerns into their behaviour. Indeed, recent research has focused on expressing and validating sets of social, legal, ethical, empathetic, and cultural (SLEEC) concerns as rules. However, existing work is limited to rule specification or verification, leaving the problem of semanticspreserving operationalisation of ethical rules in autonomous systems largely unaddressed. Thus, we provide an operational solution for ethical-aware autonomous systems, applied to the realm of multiservice robots. Specifically, we devise a principled approach, named CO-SLEEC (Context-Oriented SLEEC), linking the normative setting of SLEEC rules to context-oriented programming (COP). COSLEEC enables runtime adaptation while preserving the semantics of SLEEC rules during robot task execution. It features two reusable Python libraries for (i) parsing SLEEC rules into contextual elements for operationalising them, and (ii) connecting the operational model to Robotic Operating System (ROS), respectively. We evaluate COSLEEC for correctness, efficiency, and maintainability over multi-service assistive robot scenarios.

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Cite as:

@inproceedings{CasadeiDSFPST26,
  author       = {Roberto Casadei and Martina {De Sanctis} and Gianluca Filippone and Sara Pettinari and {Gian Luca} Scoccia and Nicolas Troquard
  },
  title        = {Operationalising Normative Rules in Autonomous Robotic Systems through Context-Oriented Programming},
  booktitle    = {International Joint Conference on Artificial Intelligence, {IJCAI} 2026},
  pages        = {toappear},
  publisher    = {ijcai.org},
  year         = {2026},
}