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Stein Variational Goal Generation For Reinforcement Learning in Hard Exploration Problems. (arXiv:2206.06719v1 [cs.LG])
June 15, 2022, 1:10 a.m. | Nicolas Castanet, Sylvain Lamprier, Olivier Sigaud
cs.LG updates on arXiv.org arxiv.org
Multi-goal Reinforcement Learning has recently attracted a large amount of
research interest. By allowing experience to be shared between related training
tasks, this setting favors generalization for new tasks at test time, whenever
some smoothness exists in the considered representation space of goals.
However, in settings with discontinuities in state or goal spaces (e.g. walls
in a maze), a majority of goals are difficult to reach, due to the sparsity of
rewards in the absence of expert knowledge. This implies …
arxiv exploration generation learning lg reinforcement reinforcement learning
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