TL;DR
It is suggested that chatbot communication style influences users’ perceptions of conversational agents and may improve performance relative to less supportive chatbot designs, but the overall value of chatbot interaction depends on the task context.
The findings suggest that the primary benefit of human--agent interfaces may be reducing interaction effort rather than improving speed, and that delegation reflects who the user is more than what the task demands.
In multimodal human-agent interaction, feedback plays a critical role in guiding user behavior, with its effectiveness depending not only on the content delivered but also on how it is conveyed across modalities and agent embodiments. Feedback intervention, delivering performance-related information to guide behavior,...
Ubiquitous robotic systems often lack traditional visual interfaces, necessitating resilient natural language interaction for maintenance and repair tasks. This paper presents a goal oriented agentic AI architecture designed to enable non-expert users to perform technical repairs through situated dialogue. The framewor...
Human-agent teams are collaborative systems where humans and agents work interdependently to achieve shared goals. The success of such teams is associated with the human's perception of the agent as a legitimate teammate. This perception is thought to depend not only on the agent's capabilities and reliability but also...
Conversational fillers, such as short vocalizations (e.g., “uh,” “um”) or brief phrases that manage conversational flow, are increasingly used in embodied virtual agents. Yet, their effects on users’ perceptions remain insufficiently understood. Thus, we investigated how different conversational filler strategies shape...
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