Author

Zhifeng Zhao

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Open access Mar 2025

Multi-Agent Uncertainty-Aware Pessimistic Model-Based Reinforcement Learning for Connected Autonomous Vehicles

MA-PMBRL, a novel Multi-Agent Pessimistic Model-Based Reinforcement Learning framework for CAVs, incorporating a max-min optimization approach to enhance robustness and decision-making is proposed, demonstrating that the proposed framework represents a significant step toward scalable, efficient, and reliable multi-age...

Ruo-Qi Wen, Rong-Peng Li, Xing Xu et al. · IEEE Transactions on Mobile... · 1 citation

Preprint Aug 2026

Agentic Router: An Execution-Grounded Continual Learning Approach With Memory

An execution-grounded dual-path consequence-aware agent for CLI-based SONiC operations, which generates multiple complete actions, predicts their execution consequences, and selects the final action through utility- and risk-aware reranking is proposed.

Yuxuan Chen, Rong-Peng Li, Zhi-Feng Zhao et al. · 0 citations

#machine learning Preprint Aug 2026

WONDER: A Radio World Model-based Negotiation Framework for Multi-Agent UAV Coverage Optimization

A raido World-model-based Optimized Negotiation framework for Distributed UAV covERage (WONDER), which uses a Joint-Embedding Predictive Architecture (JEPA)-based radio world model to learn and predict the incremental radio effect of each candidate trajectory from deployment-available information and builds RadioDynami...

Jiahao Huang, Rongpeng Li, Zhifeng Zhao et al. · 0 citations