Forecasting in Offline Reinforcement Learning for Non-stationary Environments

NeurIPSSpotlight2025

Authors
Suzan Ece Ada, Georg Martius, Emre Ugur, Erhan Oztop
Venue
NeurIPS 2025
Track
Spotlight

TL;DR

Offline Reinforcement Learning (RL) provides a promising avenue for training policies from pre-collected datasets when gathering additional interaction data is infeasible…

Opening excerpt from the authors’ abstract. source

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Topics

offline reinforcement learning reinforcement learning dataset

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