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pro vyhledávání: '"Abbass, Hussein A."'
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
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
Externí odkaz:
http://arxiv.org/abs/2211.12560
Autor:
Dong, Xingshuai, Garratt, Matthew A., Anavatti, Sreenatha G., Abbass, Hussein A., Dong, Junyu
Monocular depth estimation is an important task that can be applied to many robotic applications. Existing methods focus on improving depth estimation accuracy via training increasingly deeper and wider networks, however these suffer from large compu
Externí odkaz:
http://arxiv.org/abs/2209.14829
Autor:
Dam, Tanmoy, Ferdaus, Md Meftahul, Pratama, Mahardhika, Anavatti, Sreenatha G., Jayavelu, Senthilnath, Abbass, Hussein A.
Many real-world classification problems have imbalanced frequency of class labels; a well-known issue known as the "class imbalance" problem. Classic classification algorithms tend to be biased towards the majority class, leaving the classifier vulne
Externí odkaz:
http://arxiv.org/abs/2209.01555
Swarm Analytics: Designing Information Markers to Characterise Swarm Systems in Shepherding Contexts
Contemporary swarm indicators are often used in isolation, focused on extracting information at the individual or collective levels. Consequently, these are seldom integrated to infer a top-level operating picture of the swarm, its members, and its o
Externí odkaz:
http://arxiv.org/abs/2208.12386
Neural-based learning agents make decisions using internal artificial neural networks. In certain situations, it becomes pertinent that this knowledge is re-interpreted in a friendly form to both the human and the machine. These situations include: w
Externí odkaz:
http://arxiv.org/abs/2204.00272
Research in multi-agent teaming has increased substantially over recent years, with knowledge-based systems to support teaming processes typically focused on delivering functional (communicative) solutions for a team to act meaningfully in response t
Externí odkaz:
http://arxiv.org/abs/2203.12955
Publikováno v:
In Information Sciences September 2024 679