Abstract
Humans and agents often need to work together and agree on collective decisions. Ensuring that autonomous systems work responsibly is complex especially when encountering dilemmas. This paper proposes a novel, systematic model checking approach to responsible decision making by a human-agent collective to ensure it is safe, controllable and ethical. Our approach, which is based on the MCMAS model checker, verifies the permissibility of an agent’s actions by checking the decision-making behaviour against the logical formulae specified for safety, controllability and ethical behaviour. The verification results through counterexamples and simulation results can provide a judgement, and an explanation to the AI engineer of the reasons actions are refused or allowed.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
