# Study Reveals Effect of Policy Standard Deviation on Loss of Plasticity in Online Reinforcement Learning

- Source: arXiv cs.RO
- Published: 2026-10-28T04:00:00.000Z
- RoboHot: https://robohot.news/en/items/sal51jzrbjmm5c32qqw1re0et
- Original: https://arxiv.org/abs/2610.36309

## Summary

The paper analyzes loss of plasticity (LoP) in isotropic Gaussian policies within Proximal Policy Optimization (PPO), noting that the policy standard deviation σ significantly affects the extent of LoP, with theoretical and experimental support. The experiments include LoP benchmark comparisons and real-world policy deployment on a 7-DoF robotic arm; the authors also use these findings to explain why common LoP mitigation methods are effective.