79 citations · 165 across the 24 of their papers we have counts for
6 papers · 1 filter
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…
Toward Adaptable Multi-Agent Reinforcement Learning: An Assumption-Aware Review
Siyi Hu, Mohamad A Hady, Jianglin Qiao +3
Multi-Agent Reinforcement Learning (MARL) has achieved strong performance in simulated benchmarks, yet real deployments often violate the assumptions under which algorithms are des…
Multi-Agent Reinforcement Learning for Autonomous Multi-Satellite Earth Observation: A Realistic Case Study
Mohamad A. Hady, Siyi Hu, Mahardhika Pratama +2
The exponential growth of Low Earth Orbit (LEO) satellites has revolutionised Earth Observation (EO) missions, addressing challenges in climate monitoring, disaster management, and…
Onboard Optimization and Learning: A Survey
Monirul Islam Pavel, Siyi Hu, Mahardhika Pratama +1
Onboard learning is a transformative approach in edge AI, enabling real-time data processing, decision-making, and adaptive model training directly on resource-constrained devices…
Multi-Agent Reinforcement Learning for Resources Allocation Optimization: A Survey
Mohamad A. Hady, Siyi Hu, Mahardhika Pratama +2
Multi-Agent Reinforcement Learning (MARL) has become a powerful framework for numerous real-world applications, modeling distributed decision-making and learning from interactions…
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…