# Towards Verifiably Ethical Robot Behaviour

arXiv: https://arxiv.org/abs/1504.03592 · HTML: https://mlsanity.com/paper/1504.03592/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Apr 2015.

## Built on by (most cited first, 7 of 7)

- [Conceptual Framework for Autonomous Cognitive Entities](https://mlsanity.com/paper/2310.06775/) (2023)
- [Deontic Temporal Logic for Formal Verification of AI Ethics](https://mlsanity.com/paper/2501.05765/) (2025)
- [A Fuzzy Approach to the Specification, Verification and Validation of Risk-Based Ethical Decision Making Models](https://mlsanity.com/paper/2507.01410/) (2025)
- [A Real-Time Neuro-Symbolic Ethical Governor for Safe Decision Control in Autonomous Robotic Manipulation](https://mlsanity.com/paper/2603.14221/) (2026)
- [Dr. Watson type Artificial Intellect (AI) Systems](https://mlsanity.com/paper/2106.13322/) (2021)
- [Mechanical Conscience: A Mathematical Framework for Dependability of Machine Intelligence](https://mlsanity.com/paper/2605.03847/) (2026)
- [An Abstract Architecture for Explainable Autonomy in Hazardous Environments](https://mlsanity.com/paper/2606.07211/) (2026)

## Abstract (arXiv)

Ensuring that autonomous systems work ethically is both complex and difficult. However, the idea of having an additional `governor' that assesses options the system has, and prunes them to select the most ethical choices is well understood. Recent work has produced such a governor consisting of a `consequence engine' that assesses the likely future outcomes of actions then applies a Safety/Ethical logic to select actions. Although this is appealing, it is impossible to be certain that the most ethical options are actually taken. In this paper we extend and apply a well-known agent verification approach to our consequence engine, allowing us to verify the correctness of its ethical decision-making.