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Leiji Zhang

2 accepted papers

2024

MetaCARD: Meta-Reinforcement Learning with Task Uncertainty Feedback via Decoupled Context-Aware Reward and Dynamics Components

AAAI 2024technical

Meta-Reinforcement Learning (Meta-RL) aims to reveal shared characteristics in dynamics and reward functions across diverse training tasks. This objective is achieved by meta-learning a policy that is conditioned on task representations with encoded trajectory data or context, thus allowing rapid ad…

Cited by 2SourcePDFScholar
2023

Understanding and Addressing the Pitfalls of Bisimulation-based Representations in Offline Reinforcement Learning

NeurIPS 2023poster

While bisimulation-based approaches hold promise for learning robust state representations for Reinforcement Learning (RL) tasks, their efficacy in offline RL tasks has not been up to par. In some instances, their performance has even significantly underperformed alternative methods. We aim to unde…