This paper reviews "socially interactive robots": robots for which social human-robot interaction is important. We begin by discussing the context for socially interactive robots, emphasizing the relationship to other research fields and the di#erent forms of "social robots". We then present a taxonomy of design methods and system components used to build socially interactive robots. Finally, we describe the impact of these these robots on humans and discuss open issues. An expanded version of this paper, which contains a survey and taxonomy of current applications, is available as a technical report[61].

There are currently two major approaches to robot teaching: explicitly tell the robot what to do (programming) or let the robot figure it out for itself (reinforcement learning/genetic algorithms) . In this paper we give an overview of a new approach, in which the robot instead learns novel behaviours by observing the behaviour of others: imitation learning. We summarize the psychological background of this approach, propose a definition of imitation, and identify the important issues involved in implementing imitation in robotic systems. Based on this framework, we review recent published work in this area, and describe an imitation project currently underway at the Electrotechnical Laboratory in Japan. Introduction Ever since the conception of robots, researchers have been faced with the problem of how to make them behave. That is, how to endow robots with the ability to perform complex behaviours and interact intelligently with the environment. The two most widely-used solutions t...

ing away from the specific coding of the spinal fields, the examples from neurobiology provide the framework for a motor control system based on a small number of additive primitives (or basis behaviors) sufficient for a rich output movement repertoire. Our previous work (Matari'c 1995, Matari'c 1997), inspired by the same biological results, has successfully applied the idea of basis behaviors to control of mobile robots 6 by fitting it directly into the modular behavior-based control paradigm. Applictions of schema theory (Arbib 1992) to behavior-based mobile robots (Arkin 1987) have employed a similar notion of composable behaviors, stemming from foundations in neuroscience (Arbib 1981, Arbib 1989). The idea of using such primitives for articulator control has been recently studied in robotics. Williamson (1996) and Marjanovi'c, Scassellati & Williamson (1996) developed a 6 DOF (degrees of freedom) robot arm controller. While in the biological and mobile robotics work primitives c...

This paper 1 proposes a neural architecture for a robot to learn how to imitate a sequence of movements performed by another robot or by a human. The main idea is that the imitation process does not need to be given to the system but can emerge from a mis-interpretation of the perceived situation at the level of a simple sensorimotor system. We discuss the central position of imitation processes for the understanding of our high level cognitive habilities linked to selfrecognition and to the recognition of the other as something similar to me. Another interesting aspect of this work is that the neural network used for sequences learning is directly inspired from a brain structure called the hippocampus and mainly involved in our memorization capabilities (?).

This paper discusses the phenomenological dimension of social understanding. The author’s general hypothesis is that complex forms of social unders standing that biological agents especially humans show are based on two s. mechanisms: 1 the bodily, experiential dynamics of emphatic resonance s. and 2 the biographic reconstruction of a communication situation. The latter requires the agent’s bodily experiences as the point of reference for the reconstruction process. This hypothesis is derived from discussions in philosophy, natural sciences, and cognitive science on the social embodiment of cognition and understanding. Evidence comes from studies on social cognition in primates, infants, and autistic people that are interpreted in terms of the ``mind-experiencing’ ’ hypothesis. The second part of the The writing of this paper was supported by an HCMr TMR research grant. Thanks to Erich Prem and an anonymous reviewer for their comments and suggestions, which helped me to improve a previous version of this paper. I am grateful to both the AI-Lab at GMD in Germany and the VUB AI-Lab in Belgium for giving me an environment for doing my research on social agents. The seesaw scenario was part of a student project s Claus Divossen, Susanne Jucknath, Michael Savels. in collaboration with the University of Bonn, Germany. I thank Sanjida O’Connell for discussions on empathy and theory of mind. Armin Deierling provided me with information about autism resources and discussed with me the question of how people with autism probably perceive the world.

This chapter addresses embodied social interaction inlif6 like agents. Embodiment is discussedf rom both arti cial intelligence and psychology viewpoints. Di#erent degreesof embodiment in biological, virtual and robotic agents are discussed, given the example of a bottomup, behavior-oriented, dynamic control of virtual robots. A `dancing with strangers' experiment shows how the same principles can be applied to physical robot-human interaction. We then discuss the issue of sociality which di#ers in di#erent academic communities with respect to which roles are attributed to genes, memes, and the individual embodied agent.

. We do not exist alone. Humans and most other animal species live in societies where the behaviour of an individual influences and is influenced by other members of the society. Within societies, an individual learns not only through classical conditioning and reinforcement, but to a large extent through observation and imitation. This paper presents an analysis of the problem of adding such imitative learning abilities to mobile robots and describes a biologically-inspired architecture we are developing for imitative learning. Our robotic testbed and learning experiments are described and discussed. 1 Introduction Interest in the field of robot learning has been growing steadily in the last few years. Adding learning abilities to robots offers certain distinct benefits, such as ffl Increasing their ability to cope with a dynamic environment where preprogrammed knowledge of the world can become obsolete or is not available at all in the first place. ffl Reducing the cost of program...

In this paper socially intelligent agents (SIA) are understood as agents which do not only from an observer point of view behave socially but which are able to recognize and identify other agents and establish and maintain relationships to other agents. The process of building socially intelligent agents is influenced by what the human as the designer considers `social', and conversely agent tools which are behaving socially can influence human conceptions of sociality. A Cognitive Technology (CT) approach towards designing SIA affords as an opportunity to study the process of 1) how new forms of interactions and functionalities and use of technology can emerge at the human-tool interface, 2) how social agents can constrain their cognitive and social potential, and 3) how social agent technology and human (social) cognition can co-evolve and co-adapt and result in new forms of sociality. Agent-human interaction requires a cognitive fit between SIA technology and the human-in-the-loop a...

This paper discusses the usefulness of communication as a social skill for embodied robotic agents. We study a teacher-learner situation in a `meaningful' (hilly) environment. The learner uses the teacher as a model, i.e. learning to communicate means in this case that the learner tries to achieve a similar `interpretation' of the environment to that of the teacher, on the basis of its own sensorymotor interactions. A simple imitative strategy (following and keeping-contact) is used as the social context in which associative learning takes place. A specific scenario (`mother-child') is proposed and implemented as an example for a situation in which the ability to communicate is advantageous for an individual robot. The communication skill develops during the experiment using a non-supervised teaching approach. Physical experiments to test the validity of the learning architecture are reported. Results are successful in terms of the learning capacities, but they point out the limitation...

This paper addresses the role of imitation as a means to enhance the learning of communication skills in autonomous robots. A series of robotic experiments are presented in which autonomous mobile robots are taught a synthetic proto-language. Learning of the language occurs through an imitative scenario where the robot replicates the teacher's movements. Imitation is here an implicit attentional mechanism which allows the robot imitator to share a similar set of proprio- and exteroceptions with the teacher. The robot grounds its understanding of the teacher's words, which describe the teacher's current observations, upon its own perceptions which are similar to those of the teacher. Learning of the robot is based on a dynamical recurrent associative memory architecture (DRAMA). Learning is unsupervised and results from the self-organization of the robot's connectionist architecture. Results show that the imitative behavior greatly improves the efficiency and speed of the learning. More...