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Graph Backup: Data Efficient Backup Exploiting Markovian Transitions. (arXiv:2205.15824v1 [cs.LG])
June 1, 2022, 1:11 a.m. | Zhengyao Jiang, Tianjun Zhang, Robert Kirk, Tim Rocktäschel, Edward Grefenstette
cs.LG updates on arXiv.org arxiv.org
The successes of deep Reinforcement Learning (RL) are limited to settings
where we have a large stream of online experiences, but applying RL in the
data-efficient setting with limited access to online interactions is still
challenging. A key to data-efficient RL is good value estimation, but current
methods in this space fail to fully utilise the structure of the trajectory
data gathered from the environment. In this paper, we treat the transition data
of the MDP as a graph, and …
More from arxiv.org / cs.LG updates on arXiv.org
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