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Deepinder Mann

2 accepted papers

2025

Horizon Reduction Makes RL Scalable

NeurIPS 2025spotlight

In this work, we study the scalability of offline reinforcement learning (RL) algorithms. In principle, a truly scalable offline RL algorithm should be able to solve any given problem, regardless of its complexity, given sufficient data, compute, and model capacity. We investigate if and how current…

Cited by 0SourceScholar