This article surveys reinforcement learning approaches in social robotics. Reinforcement
learning is a framework for decision-making problems in which an agent interacts through …

The field of artificial intelligence (AI) has gained immense traction over the past decade,
producing increasingly successful applications as research strives to understand and exploit …

Reinforcement learning agent learns how to perform a task by interacting with the
environment. The use of reinforcement learning in real-life applications has been limited …

Nonverbal sound offers great potential to enhance robots' interactions with humans, and a
growing body of research has begun to explore nonverbal sound for tasks such as sound …

Social robots are being deployed to interact with people in various scenarios, where they
are expected to in-corporate human-like conversational strategies to achieve flu-ency in …

We provide a comprehensive overview of existing systems for the computational generation
of verbal humor in the form of jokes and short humorous texts. Considering linguistic humor …

Child-robot interactions in educational, developmental, and health domains are widely
explored, but little is known about how families perceive the presence of a social robot in …

Adapting to dynamic environments is essential for artificial agents, especially those aiming
to communicate with people interactively. In this context, a social robot that adapts its …

Social robots and autonomous social agents are becoming more ingrained in our everyday
lives. Interactive agents from Siri to Anki's Cozmo robot include the ability to tell jokes to …

Current Humanoid Service Robot (HSR) behaviours mainly rely on static models that cannot
adapt dynamically to meet individual customer attitudes and preferences. In this work, we …