arXiv 2610.20584 · cs.CV · 2026-10-14
Player-1: Learning to Play from Synthetic Experience
Mingyu Ouyang, Yiran Wang, Siyuan Hu, Xingyilang Yin, Huiqiang Sun, Guangzhi Wang, Junfu Pu, Cheng Cheng and 4 more
ARC Lab, Tencent
In latest · #6 2026-W42 #5 Added on 2026-10-21
One-line takeaway
Player-1 post-trains computer-use agents on synthetic experience so they learn to control games beyond demonstrations.
Player-1 用合成交互经验做后训练，让电脑操作型 Agent 学会玩游戏。
Read on arXiv PDF Hugging Face discussion Code Project page
Topics & disciplines
More on Agents
- Raven: The Harness of Harnesses for Composable Agentic Intelligence ▲748
- False Frontiers: Diagnosing and Mitigating Co-Cheating in Self-Evolving Search Agents ▲642
- BizAgentBench: Unveiling Hidden Challenges in Deploying Long-Horizon Agents for Real-World Business ▲490
- Omni-IO Skills: Harnessing Your Agent Omni-Native ▲485
- OpenGCUA: Toward a Fully Open Stack for Generalist Computer Use ▲330
About this data
Metadata from the arXiv API (verified); upvotes from Hugging Face Daily Papers; citations from Semantic Scholar. Last refreshed 2026-10-22.
The takeaway is written by AIMap from the abstract; the abstract itself is not reproduced — read the original.