An architecture for ethical robots inspired by the simulation theory of cognition

Vanderelst, D. and Winfield, A. F. (2018) An architecture for ethical robots inspired by the simulation theory of cognition. Cognitive Systems Research, 48. pp. 56-66. ISSN 1389-0417 Available from: http://eprints.uwe.ac.uk/31758

[img]
Preview
PDF
1-s2.0-S1389041716302005-main.pdf - Published Version
Available under License Creative Commons Attribution 4.0.

Download (1MB) | Preview

Abstract/Description

The expanding ability of robots to take unsupervised decisions renders it imperative that mechanisms are in place to guarantee the safety of their behavior. Moreover, intelligent autonomous robots should be more than safe; arguably they should also be explicitly ethical. In this paper, we propose 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 proposed Ethical Layer enables the robot to prevent the human from coming to harm in simple test scenarios.

Item Type: Article
Uncontrolled Keywords: LaTeX, template
Faculty/Department: Faculty of Environment and Technology > Department of Engineering Design and Mathematics
Depositing User: Professor A. Winfield
Date Deposited: 08 May 2017 14:44
Last Modified: 22 Nov 2018 21:14
URI: http://eprints.uwe.ac.uk/id/eprint/31758

Statistics

Downloads
Activity Overview
290Downloads
798Hits
Origin of downloads

Additional statistics for this repository are available via IRStats2

Actions (login required)

View Item View Item