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EnglishIn this paper, we address the state estimation problem for multi-agent systems interacting in large scale networks. This research is motivated by the observation that in large-scale networks for many practical applications and domains, each agent only requires information concerning agents spatially close to its location, let’s say topologically k-hop away. We propose a scalable framework where each agent is able to estimate in finitetime the state of its k-hop neighborhood by interacting only with the agents belonging to its 1-hop neighborhood.
http://hdl.handle.net/11386/4702826| Titolo: | A K-Hop Graph-Based Observer for Large-Scale Networked Systems |
| Autori: | MARINO, Alessandro (Corresponding) |
| Data di pubblicazione: | 2017 |
| Abstract: | In this paper, we address the state estimation problem for multi-agent systems interacting in large scale networks. This research is motivated by the observation that in large-scale networks for many practical applications and domains, each agent only requires information concerning agents spatially close to its location, let’s say topologically k-hop away. We propose a scalable framework where each agent is able to estimate in finitetime the state of its k-hop neighborhood by interacting only with the agents belonging to its 1-hop neighborhood. |
| Handle: | http://hdl.handle.net/11386/4702826 |
| ISBN: | 978-1-5090-2872-6 |
| Appare nelle tipologie: | 4.1 Contributi in Atti di convegno |
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