DRAMA, a connectionist architecture for online learning and control of autonomous robots: experiments on learning of a synthetic proto-language with a doll robot

Currently, academic as well as industrial research investigates the design of social skills for a robot, which could facilitate the robot's interaction with humans. Work in this area pointed out three important abilities required by the robot, namely the capacity for communicating, for learning and for imitating. The work presented in this paper integrates these three aspects by building robots capable of learning a language through the observation and imitation of a teacher agent. This paper presents DRAMA, an artificial neural network architecture which allows online learning of spatio-temporal regularities and time series in a robot's sequence of perceptions. The model has been implemented in a number of experiments, using wheeled robots, in which the robot learned the topography of its environment relative to fixed landmarks. This paper presents the latest implementation of the model in Robota, a doll robot, which is taught a synthetic proto-language.