3 papers
cs.LG2026
Hybrid Energy-Aware Reward Shaping: A Unified Lightweight Physics-Guided Methodology for Policy Optimization
Qijun Liao, Jue Yang, Yiting Kang +3
Deep reinforcement learning for continuous control often suffers from high variance, low energy efficiency, and poor generalization under distribution shift, as purely data-driven…
cs.NI2025
DRAMA: A Dynamic Packet Routing Algorithm using Multi-Agent Reinforcement Learning with Emergent Communication
Wang Zhang, Chenguang Liu, Yue Pi +6
The continuous expansion of network data presents a pressing challenge for conventional routing algorithms. As the demand escalates, these algorithms are struggling to cope. In thi…
cs.NI2024
Applications of Multi-Agent Deep Reinforcement Learning Communication in Network Management: A Survey
Yue Pi, Wang Zhang, Yong Zhang +4
With the advancement of artificial intelligence technology, the automation of network management, also known as Autonomous Driving Networks (ADN), is gaining widespread attention.…