5 papers
Building Large-Scale Drone Defenses from Small-Team Strategies
Grant Douglas, Stephen Franklin, Claudia Szabo +1
Defending against large adversarial drone swarms requires coordination methods that scale effectively beyond conventional multi-agent optimisation. In this paper, we propose to sca…
Evolving LLM-Derived Control Policies for Residential EV Charging and Vehicle-to-Grid Energy Optimization
Vishesh Purnananda, Benjamin John Wruck, Mingyu Guo
This research presents a novel application of Evolutionary Computation to the domain of residential electric vehicle (EV) energy management. While reinforcement learning (RL) achie…
MTDrive: Multi-turn Interactive Reinforcement Learning for Autonomous Driving
Xidong Li, Mingyu Guo, Chenchao Xu +5
Trajectory planning is a core task in autonomous driving, requiring the prediction of safe and comfortable paths across diverse scenarios. Integrating Multi-modal Large Language Mo…
Co-Evolutionary Defence of Active Directory Attack Graphs via GNN-Approximated Dynamic Programming
Diksha Goel, Hussain Ahmad, Kristen Moore +1
Modern enterprise networks increasingly rely on Active Directory (AD) for identity and access management. However, this centralization exposes a single point of failure, allowing a…
Symmetry-Breaking Augmentations for Ad Hoc Teamwork
Ravi Hammond, Dustin Craggs, Mingyu Guo +2
In dynamic collaborative settings, for artificial intelligence (AI) agents to better align with humans, they must adapt to novel teammates who utilise unforeseen strategies. While…