Tackling Challenges of Robustness Measures for Autonomous Agent Collaboration in Open Multi-Agent Systems

dc.contributor.author Jin, David
dc.contributor.author Kannengießer, Niclas
dc.contributor.author Sturm, Benjamin
dc.contributor.author Sunyaev, Ali
dc.date.accessioned 2021-12-24T18:29:18Z
dc.date.available 2021-12-24T18:29:18Z
dc.date.issued 2022-01-04
dc.description.abstract Open multi-agent systems (OMASs) allow autonomous agents (AAs) to collaborate in coalitions to accomplish complex tasks (e.g., swarm robots exploring new terrain). In OMASs, AAs can arbitrarily join and leave the network. Thus, AAs must often collaborate with unknown AAs that may corrupt coalitions, leading to less robust systems. However, measures to improve robustness of OMASs are subject to challenges, decreasing their effectiveness. To understand how to improve coalition robustness in OMASs and address challenges of existing robustness measures, we carried out a literature review and revealed three types of robustness measures (i.e., collaboration coordination, normative control, and reliability prediction). Moreover, we found 21 challenges for the identified robustness measures and 24 corresponding solutions. By carrying out this literature review, we forge new connections between existing measures and identify challenges and measures that apply to multiple existing measures. Hereby, our work supports more robust collaborations between AAs in open systems.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2022.911
dc.identifier.isbn 978-0-9981331-5-7
dc.identifier.uri http://hdl.handle.net/10125/80253
dc.language.iso eng
dc.relation.ispartof Proceedings of the 55th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Cybersecurity and Software Assurance
dc.subject autonomous agents
dc.subject multi-agent systems
dc.subject openess
dc.subject robustness
dc.title Tackling Challenges of Robustness Measures for Autonomous Agent Collaboration in Open Multi-Agent Systems
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