11 citations · 12 across the 5 of their papers we have counts for
5 papers
Enhancing IoT-Botnet Detection using Variational Auto-encoder and Cost-Sensitive Learning: A Deep Learning Approach for Imbalanced Datasets
Hassan Wasswa, Timothy Lynar, Hussein Abbass
The Internet of Things (IoT) technology has rapidly gained popularity with applications widespread across a variety of industries. However, IoT devices have been recently serving a…
Planning-Assisted Context-Sensitive Autonomous Shepherding of Dispersed Robotic Swarms in Obstacle-Cluttered Environments
Jing Liu, Hemant Singh, Saber Elsayed +2
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 recen…
Contextually Aware Intelligent Control Agents for Heterogeneous Swarms
Adam Hepworth, Aya Hussein, Darryn Reid +1
An emerging challenge in swarm shepherding research is to design effective and efficient artificial intelligence algorithms that maintain a low-computational ceiling while increasi…
Swarm Analytics: Designing Information Markers to Characterise Swarm Systems in Shepherding Contexts
Adam Hepworth, Aya Hussein, Darryn Reid +1
Contemporary swarm indicators are often used in isolation, focused on extracting information at the individual or collective levels. Consequently, these are seldom integrated to in…
Disturbances in Influence of a Shepherding Agent is More Impactful than Sensorial Noise During Swarm Guidance
Hung The Nguyen, Matthew Garratt, Lam Thu Bui +1
The guidance of a large swarm is a challenging control problem. Shepherding offers one approach to guide a large swarm using a few shepherding agents (sheepdogs). While noise is an…