Sample Complexity of Equivariant Reinforcement Learning

arXiv:2609.36421 · cs.CC, cs.LG, math.GR · Submitted 2026-09-29 · Read on arXiv

cs.CC, cs.LG, math.GR

Submitted: 2026-09-29

Updated: 2026-09-29

Terminology

• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Sample Complexity — 1× in this paper · explained in 17 episodes

Sources

• Relational inductive biases, deep learning, and graph networks
• Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
• $\pi_\texttt{RL}$: Online RL Fine-tuning for Flow-based Vision-Language-Action Models
• Platonic Transformers: A Solid Choice For Equivariance
• Graph Convolutional Reinforcement Learning
• QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation
• MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations
• Empirical Bernstein Bounds and Sample Variance Penalization
• Scaling Laws and Symmetry, Evidence from Neural Force Fields
• Value-Based Deep RL Scales Predictably
• Proximal Policy Optimization Algorithms
• Probing Equivariance and Symmetry Breaking in Convolutional Networks
• $\mathrm{SO}(2)$-Equivariant Reinforcement Learning
• Understanding deep learning requires rethinking generalization

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