目的智能系统在智能制造, 智慧城市, 医疗健康, 生活服务等各种场景中越来越广泛地存在,
为应对人与智能系统的交互中所面临的诸多挑战, 从技术和体验的视角分析人机智能协同中的 …

We present a dialogue system for a conversational robot, Erica. Our goal is for Erica to
engage in more human-like conversation, rather than being a simple question-answering …

Communication with robots is challenging, partly due to their differences from humans and
the consequent discrepancy in people's mental model of what robots can see, hear, or …

When human partners attend to peripheral computing devices while interacting with
conversational robots, the inability of the robots to determine the actual engagement level of …

Experts from a range of disciplines explore how humans and artificial agents can quickly
learn completely new tasks through natural interactions with each other. Humans are not …

Situated multimodal systems that instruct humans need to handle user uncertainties, as
expressed in behaviour, and plan their actions accordingly. Speakers' decision to …

Remarkable advancements in modern generative foundation models have enabled the
development of sophisticated and highly capable autonomous agents that can observe their …

This chapter focuses on the main challenges and research opportunities in enabling natural
interaction to support interactive task learning. Interaction is an exchange of communicative …

Robot Learning from Demonstration (RLfD) allows non-expert users to teach a robot new
skills or tasks directly through demonstrations. Although modeled after human–human …

In previous chapters, we have discussed how a chatbot can learn world knowledge (eg,
entities, facts, concepts) to generate more relevant responses and answer user questions (in …