In this article we expose some interesting ideas by Maja J. Mataric (University of Southern California) about the design of social robots (see Mataric, 2002 in Encyclopedia of cognitive science).
Building sociable robots includes many facets, like imitation, social learning and emotion. We can design social robots applying ideas from developmental psychology, for example and so looking for inspiration in Neuroscience. Mataric (1992) described the work with TOTO, a mobile robot being able to represent landmarks in the environment. TOTO was representative of an Artificial Intelligence interpretation of the organization of the rat hippocampus. As an alternative, Nicolescu and Mataric (2002) designed a hierarchical behavior-based architecture enabling behaviors to represent more abstract concepts. Here representations are stored in a distribuited fashion. The same perspective on generating behavior has been successful with groups of robots. This area is known as "swarm robotics". Truly coordinating a set of robots is complicated problem. Multi-robot coordination involves communication and selection action, between several tasks. In 1995 Mataric worked with the NERD HERD, a group of 20 autonomous mobile robots with limited sensing and computational abilities. Each robot was programmed with a small set of behaviors: homing, wandering, following, aggregation and dispersion. The basis behaviors were designed to conserve energy by minimizing interference between robots. Mataric (1997) described the problem of learning social rules in order to maximize energy. Robots acting within a social setting have additional sources of information: observation of a peer performing a successful action, etc. Models of people´s natural social interactions are relevant for robots in human environments. For humanoid robots this can take the form of learning natural human skills. Mataric is an excellent searcher looking for solutions which imply the design of social robots.
