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cs.LG2024
Stable Continual Reinforcement Learning via Diffusion-based Trajectory Replay
Feng Chen, Fuguang Han, Cong Guan +4
Given the inherent non-stationarity prevalent in real-world applications, continual Reinforcement Learning (RL) aims to equip the agent with the capability to address a series of s…
cs.LG2024
Quality-Diversity with Limited Resources
Ren-Jian Wang, Ke Xue, Cong Guan +1
Quality-Diversity (QD) algorithms have emerged as a powerful optimization paradigm with the aim of generating a set of high-quality and diverse solutions. To achieve such a challen…