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cs.AI2024
Offline-to-Online Multi-Agent Reinforcement Learning with Offline Value Function Memory and Sequential Exploration
Hai Zhong, Xun Wang, Zhuoran Li +1
Offline-to-Online Reinforcement Learning has emerged as a powerful paradigm, leveraging offline data for initialization and online fine-tuning to enhance both sample efficiency and…
cs.LG2024
Beyond Squared Error: Exploring Loss Design for Enhanced Training of Generative Flow Networks
Rui Hu, Yifan Zhang, Zhuoran Li +1
Generative Flow Networks (GFlowNets) are a novel class of generative models designed to sample from unnormalized distributions and have found applications in various important task…