Negotiated collusion: Modeling social language and its relationship effects in intelligent agents
Negotiated collusion: Modeling social language and its relationship effects in intelligent agents
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DOI：
10.1023/a:1024026532471
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发表时间：
2003-02-01
影响因子：
3.6
通讯作者：
Bickmore, T
中科院分区：
文献类型：
--
作者：
Cassell, J;Bickmore, T
与用户建立协作信任关系在广泛的应用程序中是至关重要的，例如建议提供或金融交易，并且在所有应用程序中甚至需要最低程度的合作才能发起和维护与用户的交互。尽管人与人之间关系的这一方面很重要，但很少有智能系统试图建立信任、可信度或其他类似人际变量的用户模型，或在与用户交互时影响这些变量。人类使用包括闲聊在内的各种社交语言来建立相互信任的协作性人际关系。我们认为，智能代理也可以使用这样的策略，考虑到可以用来管理对话的无数多模式线索，具体化的会话代理非常适合这项任务。本文描述了一种社会语言与人际关系之间的关系模型，一种能够生成社会语言以实现人际目标的新型话语规划器，并在一个具体的会话代理中进行了实际实现。我们讨论了对我们的系统的评估，其中社交语言的使用被证明对用户对代理的知识和接触用户的能力的感知有显著影响，对他们的信任、可信度以及他们对系统了解他们的感觉有多好，对于表现出特定个性特征的用户。
Building a collaborative trusting relationship with users is crucial in a wide range of applications, such as advice-giving or financial transactions, and some minimal degree of cooperativeness is required in all applications to even initiate and maintain an interaction with a user. Despite the importance of this aspect of human-human relationships, few intelligent systems have tried to build user models of trust, credibility, or other similar interpersonal variables, or to influence these variables during interaction with users. Humans use a variety of kinds of social language, including small talk, to establish collaborative trusting interpersonal relationships. We argue that such strategies can also be used by intelligent agents, and that embodied conversational agents are ideally suited for this task given the myriad multimodal cues available to them for managing conversation. In this article we describe a model of the relationship between social language and interpersonal relationships, a new kind of discourse planner that is capable of generating social language to achieve interpersonal goals, and an actual implementation in an embodied conversational agent. We discuss an evaluation of our system in which the use of social language was demonstrated to have a significant effect on users' perceptions of the agent's knowledgableness and ability to engage users, and on their trust, credibility, and how well they felt the system knew them, for users manifesting particular personality traits.