Alan Winfield Alan.Winfield@uwe.ac.uk
Professor in Robotics
An architecture for ethical robots inspired by the simulation theory of cognition
Winfield, Alan; Vanderelst, Dieter
Authors
Dieter Vanderelst
Abstract
The expanding ability of robots to take unsupervised decisions renders it imperative that mechanisms are in place to guarantee the safety of their behaviour. Moreover, intelligent autonomous robots should be more than safe; arguably they should also be explicitly ethical. In this paper, we put forward a method for implementing ethical behaviour in robots inspired by the simulation theory of cognition. In contrast to existing frameworks for robot ethics, our approach does not rely on the verification of logic statements. Rather, it utilises internal simulations which allow the robot to simulate actions and predict their consequences. Therefore, our method is a form of robotic imagery. To demonstrate the proposed architecture, we implement a version of this architecture on a humanoid NAO robot so that it behaves according to Asimov's laws of robotics. In a series of four experiments, using a second NAO robot as a proxy for the human, we demonstrate that the Ethical Layer enables the robot to prevent the human from coming to harm in simple test scenarios.
Citation
Winfield, A., & Vanderelst, D. (2018). An architecture for ethical robots inspired by the simulation theory of cognition. Cognitive Systems Research, 48, 56-66. https://doi.org/10.1016/j.cogsys.2017.04.002
Journal Article Type | Article |
---|---|
Acceptance Date | Apr 8, 2017 |
Online Publication Date | May 22, 2017 |
Publication Date | May 1, 2018 |
Deposit Date | May 8, 2017 |
Publicly Available Date | Mar 29, 2024 |
Journal | Cognitive Systems Research |
Print ISSN | 1389-0417 |
Electronic ISSN | 1389-0417 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 48 |
Pages | 56-66 |
DOI | https://doi.org/10.1016/j.cogsys.2017.04.002 |
Keywords | Ethical robots; Self-simulation; Simulation theory; Machine ethics; Machine Morality |
Public URL | https://uwe-repository.worktribe.com/output/1435374 |
Publisher URL | https://doi.org/10.1016/j.cogsys.2017.04.002 |
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Licence
http://creativecommons.org/licenses/by/4.0/
Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/
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