用形式化方法验证聊天机器人是否真正共情，提升心理治疗助手的可靠性。
Do You Understand How I Feel?: Towards Verified Empathy in Therapy Chatbots
- 用Transformer提取对话特征，构建双人治疗会话的随机混合自动机模型。
- 通过统计模型检测，发现人工策略可提升共情属性满足概率。
- 适合研究心理AI伦理、形式化验证或医疗对话系统的人参考。
对话智能体正越来越多地用于心理健康支持路径，具有重要社会影响。在治疗场景中，共情是关键的非功能需求，但当前聊天机器人开发缺乏系统性方法来定义和验证共情能力。本文提出一个融合自然语言处理与形式化验证的框架，实现可验证的共情式治疗聊天机器人。基于Transformer的模型提取对话特征，并转化为双人治疗会话的随机混合自动机（Stochastic Hybrid Automaton）模型。通过统计模型检查（Statistical Model Checking）验证共情相关性质，同时利用策略合成指导代理行为优化。初步结果表明，该形式化模型能以较高保真度捕捉治疗动态，且人工设计策略显著提升了满足共情要求的概率。
原文摘要 · Abstract (English)
Conversational agents are increasingly used as support tools along mental therapeutic pathways with significant societal impacts. In particular, empathy is a key non-functional requirement in therapeutic contexts, yet current chatbot development practices provide no systematic means to specify or verify it. This paper envisions a framework integrating natural language processing and formal verification to deliver empathetic therapy chatbots. A Transformer-based model extracts dialogue features, which are then translated into a Stochastic Hybrid Automaton model of dyadic therapy sessions. Empathy-related properties can then be verified through Statistical Model Checking, while strategy synthesis provides guidance for shaping agent behavior. Preliminary results show that the formal model captures therapy dynamics with good fidelity and that ad-hoc strategies improve the probability of satisfying empathy requirements.
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