AI角色扮演的深层人格：三层架构让AI不再一秒出戏
现在的AI角色扮演大多靠一句「你是个开朗的人」这种浅层设定，聊几句就崩。这篇把人格拆成三层：外在言行、潜在信念、核心动机，像给人写剧本一样给AI一套内部脚本，让它只能在这个框架里反应，而不是自由发挥。结果发现：AI的对话流畅度已经接近人类，但在情绪表达和共同注意力上系统性拉胯——它说得出漂亮话，却接不住你的情绪。
📄 原文摘要(英文)
Existing approaches to persona simulation with Large Language Models (LLMs) mostly rely on shallow character descriptions that fail to sustain coherent character behavior across extended interactions. We introduce Deep Persona, a psychologically grounded, three-layered architecture that organizes personas into hierarchical levels of observable expression, latent beliefs, and core motivational drives, for constructing highly convincing role-playing agents. Governed by the principles of scripted determinism and bounded agency, the architecture restricts the model to a reactive engine guided by a structured internal script. We further propose a reference-free evaluation framework that benchmarks dialogue naturalness against empirical human distributions using established psychological clinical instruments and adversarial stress-tests. Empirical evaluation reveals that while LLMs achieve high pragmatic fluency, they exhibit systematic limitations in emotional expression and joint attention. In addition, we present a case study of two Deep Personas and evaluate them using the proposed framework, demonstrating that structured personas can produce interactions that more closely align with human conversational behavior.