Learning Descriptors for Novelty-Search Based Instance Generation via Meta-evolution
Conference Proceeding
Marrero, A., Segredo, E., León, C., & Hart, E. (in press)
Learning Descriptors for Novelty-Search Based Instance Generation via Meta-evolution. In Genetic and Evolutionary Computation Conference (GECCO ’24), July 14–18, 2024, Melbourne, VIC, Australia. https://doi.org/10.1145/3638529.3654028
The ability to generate example instances from a domain is important in order to benchmark algorithms and to generate data that covers an instance-space in order to train mach...
A Hierarchical Approach to Evolving Behaviour-Trees for Swarm Control
Conference Proceeding
Montague, K., Hart, E., & Paechter, B. (2024)
A Hierarchical Approach to Evolving Behaviour-Trees for Swarm Control. In S. Smith, J. Correia, & C. Cintrano (Eds.), Applications of Evolutionary Computation: 27th European Conference, EvoApplications 2024, Held as Part of EvoStar 2024, Aberystwyth, UK, April 3–5, 2024, Proceedings, Part I (178-193). https://doi.org/10.1007/978-3-031-56852-7_12
Behaviour trees (BTs) are commonly used as controllers in robotic swarms due their modular composition and to the fact that they can be easily interpreted by humans. From an a...
On the Utility of Probing Trajectories for Algorithm-Selection
Conference Proceeding
Renau, Q., & Hart, E. (2024)
On the Utility of Probing Trajectories for Algorithm-Selection. In Applications of Evolutionary Computation. EvoApplications 2024 (98-114). https://doi.org/10.1007/978-3-031-56852-7_7
Machine-learning approaches to algorithm-selection typically take data describing an instance as input. Input data can take the form of features derived from the instance desc...
Generalized Early Stopping in Evolutionary Direct Policy Search
Journal Article
Arza, E., Le Goff, L. K., & Hart, E. (in press)
Generalized Early Stopping in Evolutionary Direct Policy Search. ACM Transactions on Evolutionary Learning and Optimization, https://doi.org/10.1145/3653024
Lengthy evaluation times are common in many optimization problems such as direct policy search tasks, especially when they involve conducting evaluations in the physical world...
Cluster-based oversampling with area extraction from representative points for class imbalance learning
Journal Article
Farou, Z., Wang, Y., & Horváth, T. (2024)
Cluster-based oversampling with area extraction from representative points for class imbalance learning. Intelligent Systems with Applications, 22, Article 200357. https://doi.org/10.1016/j.iswa.2024.200357
Class imbalance learning is challenging in various domains where training datasets exhibit disproportionate samples in a specific class. Resampling methods have been used to a...
Synthesising Diverse and Discriminatory Sets of Instances using Novelty Search in Combinatorial Domains
Journal Article
Marrero, A., Segredo, E., Leon, C., & Hart, E. (in press)
Synthesising Diverse and Discriminatory Sets of Instances using Novelty Search in Combinatorial Domains. Evolutionary Computation,
Gathering sufficient instance data to either train algorithm-selection models or understand algorithm footprints within an instance space can be challenging. We propose an app...
A spatio-temporal graph convolutional approach to real-time load forecasting in an edge-enabled distributed Internet of Smart Grids energy system
Journal Article
Liu, Q., Pan, L., Cao, X., Gan, J., Huang, X., & Liu, X. (in press)
A spatio-temporal graph convolutional approach to real-time load forecasting in an edge-enabled distributed Internet of Smart Grids energy system. Concurrency and Computation: Practice and Experience, Article e8060. https://doi.org/10.1002/cpe.8060
As the edge nodes of the Internet of Smart Grids (IoSG), smart sockets enable all kinds of power load data to be analyzed at the edge, which create conditions for edge calcula...
Utilizing the Ensemble Learning and XAI for Performance Improvements in IoT Network Attack Detection
Conference Proceeding
Kalutharage, C. S., Liu, X., Chrysoulas, C., & Bamgboye, O. (2024)
Utilizing the Ensemble Learning and XAI for Performance Improvements in IoT Network Attack Detection. In Computer Security. ESORICS 2023 International Workshops (125-139). https://doi.org/10.1007/978-3-031-54129-2_8
Expressive Talking Avatars
Journal Article
Pan, Y., Tan, S., Cheng, S., Lin, Q., Zeng, Z., & Mitchell, K. (2024)
Expressive Talking Avatars. IEEE Transactions on Visualization and Computer Graphics, 30(5), 2538-2548. https://doi.org/10.1109/TVCG.2024.3372047
Stylized avatars are common virtual representations used in VR to support interaction and communication between remote collaborators. However, explicit expressions are notorio...
How Much do Robots Understand Rudeness? Challenges in Human-Robot Interaction
Conference Proceeding
Orme, M., Yu, Y., & Tan, Z. (in press)
How Much do Robots Understand Rudeness? Challenges in Human-Robot Interaction.
This paper concerns the pressing need to understand and manage inappropriate language within the evolving human-robot interaction (HRI) landscape. As intelligent systems and r...