The paper discusses dynamics in human-robot interaction. Firstly, we propose a terminology for classifying robot-human interaction dynamics of increasing complexity. Secondly, we address the role of human-robot interaction in a particular application area, namely rehabilitation. Specifically, we discuss the area of autism and how mobile robots can play a therapeutic role in the rehabilitation of children with autism (investigated in the project AURORA). Problems and challenges of this work in progress aiming at `getting the interaction dynamics right' are discussed. 1. Introduction: Building Interactive Robotic Systems In recent years, the concept of believability and believable characters has attracted a lot of attention in the field of autonomous agents ((Bates, 1994), (Dautenhahn, 1998), (Porter and Susman, 2000)). Increasingly, researchers are exploiting techniques which have been originally developed in Arts and animation in order to allow a `suspension of disbelief'....

We created the characters Agneta & Frida with the intent to strengthen and encourage exploration of information spaces. In a follow-up study we tried to capture whether users found the characters believable, whether they raised affective responses in users, and whether they created a richer more narratively oriented experience of the space. In order to do so, we had to develop new criteria and methods of understanding users ’ conceptions and affective responses. We discuss the study in detail, as well as the general implications for how to perform user studies and design of character-enhanced systems. 1

Communication between players in networked computer games is often inadequately implemented. The games do not exploit the full potential of using different forms of communication possibilities between players, and therefore result in problems in sending and receiving messages. This paper introduces a model that describes how visual aspects of non-verbal communication (NVC) in avatars could be systematically designed. The model can be used as a guideline in the design process of more communicative avatars.

The influence of spatial context and the role of intentionality in the interpretation of animacy from motion

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Animated interface agents have been proposed as a more natural way for the user to interact with computers. Such agents are frequently used in pedagogical and program help applications. While many aspects of social agents have been investigated, that of keeping an appropriate social distance seems to have been overlooked. This ability is coupled with an understanding of when advice is and is not wanted. An agent that gives advice in an Othello program is implemented, which using reinforcement learning adapts its frequency of suggestions to whether or not the user takes the advice. The amount of suggestions that the user can expect is visualized for the user by agent size and position. This agent is compared to one which always gives advice. In the evaluation, test participants experienced that the first agent adapted to their behavior and also found it less distracting. 1

Comprehension of goal-directed, intentional motion is an important but understudied visual function. To study it, we created a two-dimensional virtual environment populated by independently-programmed autonomous virtual agents, which navigate the environment, collecting food and competing with one another. Their behavior is modulated by a small number of distinct “mental states”: exploring, gathering food, attacking, and fleeing. In two experiments, we studied subjects ’ ability to detect and classify the agents ’ continually changing mental states on the basis of their motions and interactions. Our analyses compared subjects ’ classifications to the ground truth state occupied by the observed agent’s autonomous program. Although the true mental state is inherently hidden and must be inferred, subjects showed both high validity (correlation with ground truth) and high reliability (correlation with one another). The data provide intriguing evidence about the factors that influence estimates of mental state—a key step towards a true “psychophysics of intention.”

The paper discusses dynamics in human-robot interaction. Firstly, we propose a terminology for classifying robot-human interaction dynamics of increasing complexity. Secondly, we address the role of human-robot interaction in a particular application area, namely rehabilitation. Speci-cally, we discuss the area of autism and how mobile robots can play a therapeutic role in the rehabilitation of children with autism (investigated in the project AURORA). Problems and challenges of this work in progress aiming at `getting the interaction dynamics right ' are discussed.