Reinforcement Learning with Multi-Step Lookahead Information Via Adaptive Batching

arXiv:2601.10418 · cs.LG, stat.ML · Submitted 2026-01-15 · Read on arXiv

cs.LG, stat.ML

Submitted: 2026-01-15

Updated: 2026-10-25

Terminology

• Regret — 2× in this paper · explained in 4 episodes
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Regret Bound — 1× in this paper · explained in 2 episodes
• Regret Bounds — 1× in this paper · explained in 2 episodes

Related papers

• Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
• AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
• Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
• Convergence issues in Relational Concept Analysis based on AOC-posets
• Beliefs Beyond Posteriors: The Predictive Cost of ELBO Binding
• Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks