{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,2]],"date-time":"2025-11-02T16:47:37Z","timestamp":1762102057480},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,8]]},"abstract":"<jats:p>We develop a technique to evaluate the fault-tolerance of a multi-agent system whose number of agents is unknown at design time. We present a method for injecting a variety of non-ideal behaviours, or faults, studied in the safety-analysis literature into the abstract agent templates that are used to generate an unbounded family of multi-agent systems with different sizes. We define the parameterised fault-tolerance problem as the decision problem of establishing whether any concrete system, in which the ratio of faulty versus non-faulty agents is under a given threshold, satisfies a given temporal-epistemic specification. We put forward a sound and complete technique for solving the problem for the semantical set-up considered. We present an implementation and a case study identifying the threshold under which the alpha swarm aggregation algorithm is robust to faults against its temporal-epistemic specifications.<\/jats:p>","DOI":"10.24963\/ijcai.2017\/41","type":"proceedings-article","created":{"date-parts":[[2017,7,28]],"date-time":"2017-07-28T09:14:07Z","timestamp":1501233247000},"page":"288-294","source":"Crossref","is-referenced-by-count":2,"title":["Verifying Fault-tolerance in Parameterised Multi-Agent Systems"],"prefix":"10.24963","author":[{"given":"Panagiotis","family":"Kouvaros","sequence":"first","affiliation":[{"name":"Imperial College London"},{"name":"University of Naples Federico II"}]},{"given":"Alessio","family":"Lomuscio","sequence":"additional","affiliation":[{"name":"Imperial College London"}]}],"member":"10584","event":{"number":"26","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)","University of Technology Sydney (UTS)","Australian Computer Society (ACS)"],"acronym":"IJCAI-2017","name":"Twenty-Sixth International Joint Conference on Artificial Intelligence","start":{"date-parts":[[2017,8,19]]},"theme":"Artificial Intelligence","location":"Melbourne, Australia","end":{"date-parts":[[2017,8,26]]}},"container-title":["Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2017,7,28]],"date-time":"2017-07-28T11:51:58Z","timestamp":1501242718000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2017\/41"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2017,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2017\/41","relation":{},"subject":[],"published":{"date-parts":[[2017,8]]}}}