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cs.LG2023★ 1 cited
Efficient Symbolic Policy Learning with Differentiable Symbolic Expression
Jiaming Guo, Rui Zhang, Shaohui Peng +8
Deep reinforcement learning (DRL) has led to a wide range of advances in sequential decision-making tasks. However, the complexity of neural network policies makes it difficult to…
cs.LG2023★ 1 cited
Contrastive Modules with Temporal Attention for Multi-Task Reinforcement Learning
Siming Lan, Rui Zhang, Qi Yi +10
In the field of multi-task reinforcement learning, the modular principle, which involves specializing functionalities into different modules and combining them appropriately, has b…