arXiv cs.AI论文
行为系统需要行为测试
本文提出，AI智能体作为行为系统，应像其他行为系统一样通过系统观察、扰动和解释其行为来评估，而非仅关注性能结果。作者借鉴行为科学，提出研究议程，包括从行为序列中恢复决策策略、构建隔离行为差异的环境、探索多智能体系统的涌现动态，旨在建立AI行为科学。
这篇是正式发表的长论文，站内提供中文解读，全文请到原文阅读 PDF。
Abstract:Artificial agentic systems increasingly operate as behavioral systems by interacting with dynamic environments, pursuing goals, and adapting over time. Yet, current evaluation methods largely focus on performance outcomes, not the underlying behavioral processes that produce them. This paper argues that AI agents must be evaluated like other behavioral systems: through systematic observation, perturbation, and interpretation of their actions. We draw on lessons from the behavioral sciences to motivate this position, and propose a research agenda focused on developing rigorous behavioral tests. These include methods for recovering decision strategies from action sequences, constructing environments that isolate behavioral differences, and probing emergent dynamics in multi-agent systems. Taken together, these directions offer a roadmap for developing a science of AI behavior.