论文arxiv cs.CL · 1mo ago需要关注
AgentOdyssey: Open-Ended Long-Horizon Text Game Generation for Test-Time Continual Learning Agents
分类释义:学术论文 / 技术报告
TL;DR
arXiv:2606.24893v1 Announce Type: new Abstract: For agents to learn continuously from interaction with the world at test time, they must be able to explore effectively, acquire new world knowledge and skills, retain relevant episodic experiences, and plan over long horizons. To evaluate these key abilities of test-time continual learning agents, we introduce AgentOdyssey, a novel evaluation framework that procedurally generates open-ended text games with rich entities, world dynamics, and long-h
关键要点
- 01arXiv:2606.24893v1 Announce Type: new Abstract: For agents to learn continuously from interaction with the world at test time。
- 02they must be able to explore effectively。
- 03acquire new world knowledge and skills。
- 04retain relevant episodic experiences。
为什么值得关注
对你的工程实践意味着什么
LLM 实时生成MiniMax-M2.7缓存命中
| 角色 | 你应该做什么 |
|---|---|
| Tech Lead | 评估 AgentOdyssey 是否可作为团队 AI 智能体选型的评估标准 |
| 应用工程师 | 暂无直接影响,了解即可 |
| 运维 / 平台 | 暂无直接影响,了解即可 |
| 产品 / 业务 | 暂无直接影响,了解即可 |
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