Weiran Guo
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View article: PNAct: Crafting Backdoor Attacks in Safe Reinforcement Learning
PNAct: Crafting Backdoor Attacks in Safe Reinforcement Learning Open
Reinforcement Learning (RL) is widely used in tasks where agents interact with an environment to maximize rewards. Building on this foundation, Safe Reinforcement Learning (Safe RL) incorporates a cost metric alongside the reward metric, e…
View article: Two-Timescale Design for RIS-Aided Multicell MIMO Systems with Transceiver Hardware Impairments
Two-Timescale Design for RIS-Aided Multicell MIMO Systems with Transceiver Hardware Impairments Open
This paper investigates the reconfigurable intelligent surface (RIS)-aided uplink multicell massive multiple-input multiple-output (mMIMO) communication system with transceiver hardware impairments (THWIs), and the practical and feasible t…
View article: Two-Timescale Design for RIS-Aided Multicell MIMO Systems with Transceiver Hardware Impairments
Two-Timescale Design for RIS-Aided Multicell MIMO Systems with Transceiver Hardware Impairments Open
This paper investigates the reconfigurable intelligent surface (RIS)-aided uplink multicell massive multiple-input multiple-output (mMIMO) communication system with transceiver hardware impairments (THWIs), and the practical and feasible t…
View article: Enhancing the Robustness of QMIX against State-adversarial Attacks
Enhancing the Robustness of QMIX against State-adversarial Attacks Open
Deep reinforcement learning (DRL) performance is generally impacted by state-adversarial attacks, a perturbation applied to an agent's observation. Most recent research has concentrated on robust single-agent reinforcement learning (SARL) …