让智能体快速识别并应对设计外的陌生事件
Requirements for Recognition and Rapid Response to Unfamiliar Events Outside of Agent Design Scope
- 融合通用元知识与元推理，提升应对未知能力
- 可在缺乏知识和时间时仍实现快速可靠判断
- 适合开放世界通用智能体，提升适应性
无论过去学习如何，开放世界中的智能体终将遭遇超出过往经验、现有模型或策略范围的陌生事件。此外，智能体有时可能缺乏相关知识和足够时间来评估情境并权衡响应选项。如何让智能体在设计范围外的情境中做出合理反应？如何确保其能迅速且可靠地识别此类情况，并制定合理的自适应行动方案？本文识别出解决方案所需的关键特征，回顾了当前前沿技术，并提出一种结合领域通用元知识（受人类认知启发）与元推理的新型方法。该方法有望实现对陌生情境的快速、自适应响应，更充分满足开放世界通用智能体所需性能要求。
原文摘要 · Abstract (English)
Regardless of past learning, an agent in an open world will face unfamiliar events outside of prior experience, existing models, or policies. Further, the agent will sometimes lack relevant knowledge and/or sufficient time to assess the situation and evaluate response options. How can an agent respond reasonably to situations that are outside of its original design scope? How can it recognize such situations sufficiently quickly and reliably to determine reasonable, adaptive courses of action? We identify key characteristics needed for solutions, review the state-of-the-art, and outline a proposed, novel approach that combines domain-general meta-knowledge (inspired by human cognition) and metareasoning. This approach offers potential for fast, adaptive responses to unfamiliar situations, more fully meeting the performance characteristics required for open-world, general agents.
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