# PlayPolicy: Learning Dexterous Manipulation from Supervised Play

- Source: arXiv cs.RO
- Published: 2026-10-27T04:00:00.000Z
- RoboHot: https://robohot.news/en/items/rxgqnby0vznvo53zdzvgff81b
- Original: https://arxiv.org/abs/2610.22340

## Summary

The authors propose the PlayPolicy framework, in which a robot first learns a play policy from minutes of human play data through behavior cloning, then deploys it autonomously to collect hours of interaction data to train a world model; at inference time, this policy proposes candidate action sequences for model-predictive control (MPC).