Autonomous swarm agents using case-based reasoning

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.