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Found 5 papers, 0 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.
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.
Machine Education: Designing semantically ordered and ontologically guided modular neural networks
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.
Robotic Hierarchical Graph Neurons. A novel implementation of HGN for swarm robotic behaviour control
This new HGN is called Robotic-HGN (R-HGN), as it matches robot environment observations to environment labels via fusion of match probabilities from both temporal and intra-swarm collections.
Swarm Behaviour Evolution via Rule Sharing and Novelty Search
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 behaviour-component sharing technique.
