Zhongying Chen — accepted AI-conference papers

2026

A Unified Self-Regulating Training Framework for Federated Deep Reinforcement Learning

Meng Xu, Xinhong Chen, Zhongying Chen, Guanyi Zhao, Yang Jin, Jianping Wang

AAAI 2026technical

Federated Deep Reinforcement Learning (FDRL) aims to enable distributed collaborative training of multiple DRL models while preserving privacy. Existing FDRL methods function in static client environments, but real-world scenarios often involve dynamic state transitions, such as noise, which render

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2026

Expected Returns and Policy Inconsistency-Aware Offline Federated Deep Reinforcement Learning

Meng XU, Zhongying Chen, Weiwei Fu, Yan Li, Shuguang Wang, Jianping Wang

ICML 2026poster

Offline Federated Deep Reinforcement Learning (FDRL) methods aggregate multiple client-side offline Deep Reinforcement Learning (DRL) models, each trained locally, to facilitate knowledge sharing while preserving privacy. Existing offline FDRL methods assign client weights during global aggregation …

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