5 papers
KD-MARL: Resource-Aware Knowledge Distillation in Multi-Agent Reinforcement Learning
Monirul Islam Pavel, Siyi Hu, Muhammad Anwar Masum +3
Real world deployment of multi agent reinforcement learning MARL systems is fundamentally constrained by limited compute memory and inference time. While expert policies achieve hi…
Cross-Domain Few-Shot Learning for Hyperspectral Image Classification Based on Mixup Foundation Model
Naeem Paeedeh, Mahardhika Pratama, Ary Shiddiqi +3
Although cross-domain few-shot learning (CDFSL) for hyper-spectral image (HSI) classification has attracted significant research interest, existing works often rely on an unrealist…
Multi-Agent Reinforcement Learning for Heterogeneous Satellite Cluster Resources Optimization
Mohamad A. Hady, Siyi Hu, Mahardhika Pratama +2
This work investigates resource optimization in heterogeneous satellite clusters performing autonomous Earth Observation (EO) missions using Reinforcement Learning (RL). In the pro…
Nucleolus Credit Assignment for Effective Coalitions in Multi-agent Reinforcement Learning
Yugu Li, Zehong Cao, Jianglin Qiao +1
In cooperative multi-agent reinforcement learning (MARL), agents typically form a single grand coalition based on credit assignment to tackle a composite task, often resulting in s…
Task Allocation in Customer-led Two-sided Markets with Satellite Constellation Services
Jianglin Qiao, Zehong Cao, Dave de Jonge +1
Multi-agent systems (MAS) are increasingly applied to complex task allocation in two-sided markets, where agents such as companies and customers interact dynamically. Traditional c…