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This paper presents a swarm teaming perspective that enhances the scope ofclassic investigations on survivable networks. A target searching genericcontext is considered as test-bed, in which a swarm of ground agents and aswarm of UAVs cooperate so that the ground agents reach as many targets aspossible in the field while also remaining connected as much as possible at alltimes. To optimise the system against both these objectives in the same time,we use an evolutionary computation approach in the form of a differentialevolution algorithm. Results are encouraging, showing a good evolution of thefitness function used as part of the differential evolution, and a goodperformance of the evolved dual-swarm system, which exhibits an optimaltrade-off between target reaching and connectivity.

Optimisation of Air-Ground Swarm Teaming for Target Search, using Differential Evolution