Agent-World Scales Real-World Environment Synthesis for Evolving General Agents

Agent-World：扩展真实世界环境，让智能体与环境协同进化！

Agent-World builds 1,978 environments and 19,822 tools to train agents on long-horizon tasks. It combines web mining, tool generation, verifiable task synthesis, and GRPO training, with tasks averaging over 15 turns. The key signal is the scaling link among environment count, self-evolution rounds, and 23 benchmarks.

Why it matters: HKR-H/K/R all pass: Agent-World reports 1,978 environments, 19,822 tools, 15+ average turns, and 23 benchmarks. It is a strong agent research release, not a same-day must-write product launch.