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Исследования2026年9月9日
EnvCraft: Synthesizing Executable Environments in Agentic RL for Claw-like Agent
arXiv:2609.05576v1 Announce Type: new Abstract: The paradigm of LLMs has rapidly shifted from passive language interfaces to autonomous Claw-like agents that execute long-horizon tasks across stateful workspaces. While Agentic Reinforcement Learning (Agentic RL) provides a…
Yirong Zeng, Shen You, Jinhang Feng, Yufei Liu, Xiao Ding, Yutai Hou, Hao Cong, Yuxian Wang, Wu Ning, Wang Xu, Bibo Cai·arXiv — cs.AI
Original SourceKey Takeaways
- 01.arXiv:2609.05576v1 Announce Type: new Abstract: The paradigm of LLMs has rapidly shifted from passive language interfaces to autonomous Claw-like agents that execute long-horizon tasks across stateful workspaces
- 02.While Agentic Reinforcement Learning (Agentic RL) provides a…
This material is provided as an extended analytical summary.
Read full article at sourceAggregated within AI Qazaqstan national intelligence stream with author attribution.
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