This paper describes the development of the Microsoft XiaoIce system, the most popular social chatbot in the world. XiaoIce is uniquely designed as an AI companion with an emotional connection to satisfy the human need for communication, affection, and social belonging. We take into account both intelligent quotient (IQ) and emotional quotient (EQ) in system design, cast human-machine social chat as decision-making over Markov Decision Processes (MDPs), and optimize XiaoIce for long-term user engagement, measured in expected Conversation-turns Per Session (CPS). We detail the system architecture and key components including dialogue manager, core chat, skills, and an empathetic computing module. We show how XiaoIce dynamically recognizes human feelings and states, understands user intents, and responds to user needs throughout long conversations. Since the release in 2014, XiaoIce has communicated with over 660 million users and succeeded in establishing long-term relationships with many of them. Analysis of large-scale online logs shows that XiaoIce has achieved an average CPS of 23, which is significantly higher than that of other chatbots and even human conversations.

本文介绍了世界上最受欢迎的社交聊天机器人——微软小冰的开发过程，其独特的设计使其成为具有情感联系的人工智能伴侣，以满足人类在沟通、情感和社交归属方面的需要。通过在系统设计中同时考虑了智商和情商，将人机社交聊天视为在马尔可夫决策过程上做出决策，并优化小冰以实现长期用户参与度最大化。详细介绍了系统架构和关键组件，包括对话管理器、核心聊天、技能和一种共情计算模块。展示了小冰如何动态地识别人类情感和状态，理解用户意图，在长时间对话中回应用户需求。自2014年推出以来，小冰已与超过6.6亿活跃用户进行了沟通，并成功与其中许多建立了长期关系。大规模在线日志分析表明，小冰的平均每次会话轮次数为23，远高于其他聊天机器人甚至人类间对话。

XiaoIce的设计与实现：一款具有共情能力的社交聊天机器人