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cs.LG2026
On BatchNorm Forward Modes in Value-Based Reinforcement Learning
Daniel Palenicek, Mikael Henaff, Scott Fujimoto +1
Batch normalization (BN) substantially improves sample efficiency in continuous-control actor-critic methods such as CrossQ, yet recent studies report performance degradation in di…
cs.LG2026
The Surprising Difficulty of Search in Model-Based Reinforcement Learning
Wei-Di Chang, Mikael Henaff, Brandon Amos +2
This paper investigates search in model-based reinforcement learning (RL). Conventional wisdom holds that long-term predictions and compounding errors are the primary obstacles for…
cs.LG2025
Scalable Option Learning in High-Throughput Environments
Mikael Henaff, Scott Fujimoto, Michael Matthews +1
Hierarchical reinforcement learning (RL) has the potential to enable effective decision-making over long timescales. Existing approaches, while promising, have yet to realize the b…