22 citations · 58 across the 12 of their papers we have counts for
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cs.LG2024★ 1 cited
Position: Benchmarking is Limited in Reinforcement Learning Research
Scott M. Jordan, Adam White, Bruno Castro da Silva +2
Novel reinforcement learning algorithms, or improvements on existing ones, are commonly justified by evaluating their performance on benchmark environments and are compared to an e…
cs.LG2024
A New View on Planning in Online Reinforcement Learning
Kevin Roice, Parham Mohammad Panahi, Scott M. Jordan +2
This paper investigates a new approach to model-based reinforcement learning using background planning: mixing (approximate) dynamic programming updates and model-free updates, sim…