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Pengqin Wang

2 accepted papers

2024

Environment Transformer and Policy Optimization for Model-Based Offline Reinforcement Learning

IROS 2024poster

Interacting with the actual environment to acquire data is often costly and time-consuming in robotic tasks. Model-based offline reinforcement learning (RL) provides a feasible solution. On the one hand, it eliminates the requirements of interaction with the actual environment. On the other hand, it…

Cited by 1SourceScholar