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pro vyhledávání: '"Hunjet, Robert"'
Robotic shepherding is a bio-inspired approach to autonomously guiding a swarm of agents towards a desired location. The research area has earned increasing research interest recently due to the efficacy of controlling a large number of agents in a s
Externí odkaz:
http://arxiv.org/abs/2301.10363
Autor:
Elsayed, Saber, Singh, Hemant, Debie, Essam, Perry, Anthony, Campbell, Benjamin, Hunjet, Robert, Abbass, Hussein
Shepherding involves herding a swarm of agents (\emph{sheep}) by another a control agent (\emph{sheepdog}) towards a goal. Multiple approaches have been documented in the literature to model this behaviour. In this paper, we present a modification to
Externí odkaz:
http://arxiv.org/abs/2008.12639
The literature on machine teaching, machine education, and curriculum design for machines is in its infancy with sparse papers on the topic primarily focusing on data and model engineering factors to improve machine learning. In this paper, we first
Externí odkaz:
http://arxiv.org/abs/2002.03841
We present in this paper an exertion of our previous work by increasing the robustness and coverage of the evolution search via hybridisation with a state-of-the-art novelty search and accelerate the individual agent behaviour searches via a novel be
Externí odkaz:
http://arxiv.org/abs/1910.12412
Publikováno v:
Expert Systems with Applications 2021
This paper explores the use of a novel form of Hierarchical Graph Neurons (HGN) for in-operation behaviour selection in a swarm of robotic agents. This new HGN is called Robotic-HGN (R-HGN), as it matches robot environment observations to environment
Externí odkaz:
http://arxiv.org/abs/1910.12415
Autor:
Abpeikar, Shadi, Kasmarik, Kathryn, Garratt, Matthew, Hunjet, Robert, Khan, Md Mohiuddin, Qiu, Huanneng
Publikováno v:
In Swarm and Evolutionary Computation July 2022 72
Publikováno v:
In Expert Systems With Applications 30 December 2021 186
Publikováno v:
In ISA Transactions November 2020 106:152-170
Publikováno v:
In IFAC PapersOnLine 2020 53(2):3286-3291
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