16 citations · 29 across the 3 of their papers we have counts for
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cs.LG2020★ 11 cited
Universal Successor Features for Transfer Reinforcement Learning
Chen Ma, Dylan R. Ashley, Junfeng Wen +1
Transfer in Reinforcement Learning (RL) refers to the idea of applying knowledge gained from previous tasks to solving related tasks. Learning a universal value function (Schaul et…
cs.LG2019★ 16 cited
Learning to Combat Compounding-Error in Model-Based Reinforcement Learning
Chenjun Xiao, Yifan Wu, Chen Ma +2
Despite its potential to improve sample complexity versus model-free approaches, model-based reinforcement learning can fail catastrophically if the model is inaccurate. An algorit…