most citedScope Loss for Imbalanced Classification and RL Exploration

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cs.LG2023

Information Content Exploration

Jacob Chmura, Hasham Burhani, Xiao Qi Shi

Sparse reward environments are known to be challenging for reinforcement learning agents. In such environments, efficient and scalable exploration is crucial. Exploration is a mean…

cs.LG2023★ 1 cited

Scope Loss for Imbalanced Classification and RL Exploration

Hasham Burhani, Xiao Qi Shi, Jonathan Jaegerman +1

We demonstrate equivalence between the reinforcement learning problem and the supervised classification problem. We consequently equate the exploration exploitation trade-off in re…