mlsanityData to 14 Oct 2026

Liability, Ethics, and Culture-Aware Behavior Specification using Rulebooks

arXiv 1902.09355 ↗First posted 25 Feb 2019cs.AIcited by 43

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Abstract (arXiv)

The behavior of self-driving cars must be compatible with an enormous set of conflicting and ambiguous objectives, from law, from ethics, from the local culture, and so on. This paper describes a new way to conveniently define the desired behavior for autonomous agents, which we use on the self-driving cars developed at nuTonomy. We define a "rulebook" as a pre-ordered set of "rules", each akin to a violation metric on the possible outcomes ("realizations"). The rules are partially ordered by priority. The semantics of a rulebook imposes a pre-order on the set of realizations. We study the compositional properties of the rulebooks, and we derive which operations we can allow on the rulebooks to preserve previously-introduced constraints. While we demonstrate the application of these techniques in the self-driving domain, the methods are domain-independent.

Key facts. Cited by 43 papers in the map (data through 14 Oct 2026). First posted on arXiv 25 Feb 2019.

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Citing papers per year: 2021: 7; 2022: 6; 2023: 3; 2024: 10; 2025: 5; 2026: 12.

43 papers.

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  1. 2024Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systemscited by 96
  2. 2022LaserMix for Semi-Supervised LiDAR Semantic Segmentationcited by 93
  3. 2022Conditional Predictive Behavior Planning with Inverse Reinforcement Learning for Human-like Autonomous Drivingcited by 34
  4. 2024A Review of Reward Functions for Reinforcement Learning in the context of Autonomous Drivingcited by 18
  5. 2021The Reasonable Crowd: Towards evidence-based and interpretable models of driving behaviorcited by 12
  6. 2021Finding Critical Scenarios for Automated Driving Systems: A Systematic Literature Reviewcited by 12
  7. 2023Fine-Tuning Language Models Using Formal Methods Feedbackcited by 12
  8. 2021Safety of the Intended Driving Behavior Using Rulebookscited by 9
  9. 2021Parallel and Multi-Objective Falsification with Scenic and VerifAIcited by 8
  10. 2021Hierarchical Potential-based Reward Shaping from Task Specificationscited by 7
  11. 2022Receding Horizon Planning with Rule Hierarchies for Autonomous Vehiclescited by 7
  12. 2024Dreaming to Assist: Learning to Align with Human Objectives for Shared Control in High-Speed Racingcited by 7
31 more
  1. 2024Informed Reinforcement Learning for Situation-Aware Traffic Rule Exceptionscited by 4
  2. 2022Hybrid Deep Reinforcement Learning and Planning for Safe and Comfortable Automated Drivingcited by 3
  3. 2023Multi-Predictor Fusion: Combining Learning-based and Rule-based Trajectory Predictorscited by 3
  4. 2024GENESIS-RL: GEnerating Natural Edge-cases with Systematic Integration of Safety considerations and Reinforcement Learningcited by 3
  5. 2021Immune Moral Models? Pro-Social Rule Breaking as a Moral Enhancement Approach for Ethical AIcited by 2
  6. 2022Quantification of Actual Road User Behavior on the Basis of Given Traffic Rulescited by 2
  7. 2024Provable Traffic Rule Compliance in Safe Reinforcement Learning on the Open Seacited by 2
  8. 2024RuleFuser: An Evidential Bayes Approach for Rule Injection in Imitation Learned Planners and Predictors for Robustness under Distribution Shiftscited by 2
  9. 2021Learning to falsify automated driving vehicles with prior knowledgecited by 1
  10. 2025Predictive Traffic Rule Compliance using Reinforcement Learningcited by 1
  11. 2025Balancing Progress and Safety: A Novel Risk-Aware Objective for RL in Autonomous Drivingcited by 1
  12. 2026PoSafeNet: Safe Learning with Poset-Structured Neural Netscited by 1
  13. 2026ScenicRules: An Autonomous Driving Benchmark with Multi-Objective Specifications and Abstract Scenarioscited by 1
  14. 2026RECTOR: Priority-Aware Rule-Based Reranking for Compliance-Aware Autonomous Driving Trajectory Selectioncited by 1
  15. 2026Steering Generative Robot Policies with Lexicographic Preferencescited by 1
  16. 2022Safe Policy Improvement in Constrained Markov Decision Processescited by 0
  17. 2023Specification-Guided Data Aggregation for Semantically Aware Imitation Learningcited by 0
  18. 2024Virtue Ethics For Ethically Tunable Robotic Assistantscited by 0
  19. 2024An Ontology-based Approach Towards Traceable Behavior Specifications in Automated Drivingcited by 0
  20. 2024Incorporating System-level Safety Requirements in Perception Models via Reinforcement Learningcited by 0
  21. 2025Cross-cultural Deployment of Autonomous Vehicles Using Data-light Inverse Reinforcement Learningcited by 0
  22. 2025Integrating Legal and Logical Specifications in Perception, Prediction, and Planning for Automated Driving: A Survey of Methodscited by 0
  23. 2025Multi-Objective Search: Algorithms, Applications, and Emerging Directionscited by 0
  24. 2026Beyond Scalar Rewards: Distributional Reinforcement Learning with Preordered Objectives for Safe and Reliable Autonomous Drivingcited by 0
  25. 2026CARVE: Certified Affordable Repair of Vetoed Maneuvers via Envelopes for Interactive Drivingcited by 0
  26. 2026CARVE-Q: Quantum-Proposed, Classically Certified Interactive Driving Repaircited by 0
  27. 2026Real-Time Rulebook-Aware Nonlinear MPC for Autonomous Driving with Priority-Biased Tiered Slackscited by 0
  28. 2026Approximate Multi-Objective Search Under Rulebookscited by 0
  29. 2026Structured Four-Stage Legal Translation: From Natural-Language Traffic Rules to PROLOGcited by 0
  30. 2026Commonsense-Grounded Path Planning from Abstract Instructionscited by 0
  31. 2026MakSafe: A Spatiotemporal Semantic Framework for Formal Specification and Compliance Checking of Road Vehicle Safety Rulescited by 0