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- W4310990380 abstract "Abstract An emerging challenge in swarm shepherding research is to design effective and efficient artificial intelligence algorithms that maintain a low-computational ceiling while increasing the swarm's abilities to operate in diverse contexts. We propose a methodology to design a context-aware swarm-control intelligent agent. The intelligent control agent (shepherd) first uses swarm metrics to recognise the type of swarm it interacts with to then select a suitable parameterisation from its behavioural library for that particular swarm type. The design principle of our methodology is to increase the situation awareness (i.e. information contents) of the control agent without sacrificing the low-computational cost necessary for efficient swarm control. We demonstrate successful shepherding in both homogeneous and heterogeneous swarms." @default.
- W4310990380 created "2022-12-22" @default.
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- W4310990380 date "2022-11-28" @default.
- W4310990380 modified "2023-09-24" @default.
- W4310990380 title "Contextually Aware Intelligent Control Agents for Heterogeneous Swarms" @default.
- W4310990380 doi "https://doi.org/10.21203/rs.3.rs-2293295/v1" @default.
- W4310990380 hasPublicationYear "2022" @default.
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