FedBT: Effective and Robust Federated Unlearning via Bad Teacher Distillation for Secure Internet of Things
Journal Article
Wang, F., Huo, J., Wang, W., Zhang, X., Liu, Y., Tan, Z., & Wang, C. (in press)
FedBT: Effective and Robust Federated Unlearning via Bad Teacher Distillation for Secure Internet of Things. IEEE Internet of Things Journal,
Algorithm Selection with Probing Trajectories: Benchmarking the Choice of Classifier Model
Presentation / Conference Contribution
Renau, Q., & Hart, E. (2025, April)
Algorithm Selection with Probing Trajectories: Benchmarking the Choice of Classifier Model. Presented at EvoSTAR 2025, Trieste, Italy
Recent approaches to training algorithm selectors in the black-box optimisation domain have advocated for the use of training data that is 'algorithm-centric' in order to enca...
Beyond the Hype: Benchmarking LLM-Evolved Heuristics for Bin Packing
Presentation / Conference Contribution
Sim, K., Hart, E., & Renau, Q. (2025, April)
Beyond the Hype: Benchmarking LLM-Evolved Heuristics for Bin Packing. Presented at EvoSTAR 2025, Trieste, Italy
Coupling Large Language Models (LLMs) with Evolutionary Algorithms has recently shown significant promise as a technique to design new heuristics that outperform existing meth...
Multi-Agent Deep Reinforcement Learning-Based Cooperative Perception and Computation in VEC
Journal Article
Zhao, L., Li, L., Tan, Z., Hawbani, A., He, Q., & Liu, Z. (online)
Multi-Agent Deep Reinforcement Learning-Based Cooperative Perception and Computation in VEC. IEEE Internet of Things Journal, https://doi.org/10.1109/jiot.2025.3546915
Connected and autonomous vehicles (CAVs) are an important paradigm of intelligent transportation systems. Cooperative perception (CP) and vehicular edge computing (VEC) enhanc...
Dynamic Caching Dependency-Aware Task Offloading in Mobile EdgeComputing
Journal Article
Zhao, L., Zhao, Z., Hawbani, A., Liu, Z., Tan, Z., & Yu, K. (2025)
Dynamic Caching Dependency-Aware Task Offloading in Mobile EdgeComputing. IEEE Transactions on Computers, 74(5), 1510-1523. https://doi.org/10.1109/tc.2025.3533091
Mobile Edge Computing (MEC) is a distributed computing paradigm that provides computing capabilities at the periphery of mobile cellular networks. This architecture empowers M...
An Evaluation of Domain-agnostic Representations to Enable Multi-task Learning in Combinatorial Optimisation
Presentation / Conference Contribution
Stone, C., Renau, Q., Miguel, I., & Hart, E. (2024, June)
An Evaluation of Domain-agnostic Representations to Enable Multi-task Learning in Combinatorial Optimisation. Presented at 18th Learning and Intelligent Optimization Conference, Ischia, Italy
We address the question of multi-task algorithm selection in combinatorial optimisation domains. This is motivated by a desire to simplify the algorithm-selection pipeline by ...
A Multi-UAV Cooperative Task Scheduling in Dynamic Environments: Throughput Maximization
Journal Article
Zhao, L., Li, S., Tan, Z., Hawbani, A., Timotheou, S., & Yu, K. (2025)
A Multi-UAV Cooperative Task Scheduling in Dynamic Environments: Throughput Maximization. IEEE Transactions on Computers, 74(2), 442 - 454. https://doi.org/10.1109/tc.2024.3483636
Unmanned aerial vehicle (UAV) has been considered a promising technology for advancing terrestrial mobile computing in the dynamic environment. In this research field, through...
Evaluating the Robustness of Deep-Learning Algorithm-Selection Models by Evolving Adversarial Instances
Presentation / Conference Contribution
Hart, E., Renau, Q., Sim, K., & Alissa, M. (2024, September)
Evaluating the Robustness of Deep-Learning Algorithm-Selection Models by Evolving Adversarial Instances. Presented at 18th International Conference on Parallel Problem Solving From Nature PPSN 2024, Hagenburg, Austria
Deep neural networks (DNN) are increasingly being used to perform algorithm-selection in combinatorial optimisation domains, particularly as they accommodate input representat...
Synthesising Diverse and Discriminatory Sets of Instances using Novelty Search in Combinatorial Domains
Journal Article
Marrero, A., Segredo, E., Leon, C., & Hart, E. (2025)
Synthesising Diverse and Discriminatory Sets of Instances using Novelty Search in Combinatorial Domains. Evolutionary Computation, 33(1), 55–90. https://doi.org/10.1162/evco_a_00350
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 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...