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Found 16 papers, 1 papers with code
Planning-Assisted Context-Sensitive Autonomous Shepherding of Dispersed Robotic Swarms in Obstacle-Cluttered Environments
Robotic shepherding is a bio-inspired approach to autonomously guiding a swarm of agents towards a desired location.
Contextually Aware Intelligent Control Agents for Heterogeneous Swarms
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.
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.
Fusing Interpretable Knowledge of Neural Network Learning Agents For Swarm-Guidance
Neural-based learning agents make decisions using internal artificial neural networks.
Agile, Antifragile, Artificial-Intelligence-Enabled, Command and Control
Artificial Intelligence (AI) is rapidly becoming integrated into military Command and Control (C2) systems as a strategic priority for many defence forces.
Path Planning for Shepherding a Swarm in a Cluttered Environment using Differential Evolution
We then argue that given complexity arising from obstacles laden environments, path planning approaches could further enhance this model.
Disturbances in Influence of a Shepherding Agent is More Impactful than Sensorial Noise During Swarm Guidance
We then systematically study the impact of sensorial and actuation noise on performance.
A Comprehensive Review of Shepherding as a Bio-inspired Swarm-Robotics Guidance Approach
The simultaneous control of multiple coordinated robotic agents represents an elaborate problem.
Machine Teaching in Hierarchical Genetic Reinforcement Learning: Curriculum Design of Reward Functions for Swarm Shepherding
The design of reward functions in reinforcement learning is a human skill that comes with experience.
Transparent Machine Education of Neural Networks for Swarm Shepherding Using Curriculum Design
Swarm control is a difficult problem due to the need to guide a large number of agents simultaneously.
Lifelong Testing of Smart Autonomous Systems by Shepherding a Swarm of Watchdog Artificial Intelligence Agents
In this paper, we propose the architecture for a watchdog AI (WAI) agent dedicated to lifelong functional testing of SAS.
Mixed Initiative Systems for Human-Swarm Interaction: Opportunities and Challenges
Human-swarm interaction (HSI) involves a number of human factors impacting human behaviour throughout the interaction.
Human-Computer Interaction
Networking the Boids is More Robust Against Adversarial Learning
Swarm behavior using Boids-like models has been studied primarily using close-proximity spatial sensory information (e. g. vision range).
Computational Red Teaming in a Sudoku Solving Context: Neural Network Based Skill Representation and Acquisition
The neural network based skills are then coupled with a hard-coded constraint propagation computational Sudoku solver, in which the solving sequence is kept hard-coded, and the skills are represented through neural networks.
A Multi-Disciplinary Review of Knowledge Acquisition Methods: From Human to Autonomous Eliciting Agents
This paper offers a multi-disciplinary review of knowledge acquisition methods in human activity systems.
Shaping Influence and Influencing Shaping: A Computational Red Teaming Trust-based Swarm Intelligence Model
Influencing and shaping are social operators acting on sociotechnical systems to design a change.
