O’Connor, Daniel, Kapetanakis, Stelios, Samakovitis, Georgios ORCID: https://orcid.org/0000-0002-0076-8082, Floyd, Michael, Ontañon, Santiago and Petridis, Miltos (2018) Autonomous swarm agents using case-based reasoning. In: Artificial Intelligence XXXV: 38th SGAI International Conference on Artificial Intelligence, AI 2018, Cambridge, UK, December 11-13, 2018, Proceedings. Lecture Notes in Computer Science . Springer, Cham, pp. 210-216. ISBN 978-3030041908 (doi:10.1007/978-3-030-04191-5_20)

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Abstract

Dynamic planning is a hot topic in autonomous computing. This work presents a novel approach of simulating swarm computing behaviour in a sandbox environment where swarms of robots are challenged to fight against each other with a goal of “conquering” any environment bases. Swarm strategies are being used which are decided, modified and applied at run time. Autonomous swarm agents seem surprisingly applicable to several problems where combined artificial intelligence agents are challenged to generate innovative solutions and evaluate them prior to proposing or adopting the best possible one. This work is applicable in areas where AI agents should make selections close to real time within a range of available options under a multi-constraint, multi-objective mission environment. Relevance to Business Process workflows is also presented and documented.

Item Type:	Conference Proceedings
Title of Proceedings:	Artificial Intelligence XXXV: 38th SGAI International Conference on Artificial Intelligence, AI 2018, Cambridge, UK, December 11-13, 2018, Proceedings
Uncontrolled Keywords:	Case-based reasoning; Swarm Intelligence; Swarm robotics; Multi-agent systems; Real-time strategy; Goal-driven agent; Autonomous computing
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS) Faculty of Engineering & Science
Last Modified:	04 Mar 2022 13:06
URI:	http://gala.gre.ac.uk/id/eprint/22984

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