The study of imitation and other mechanisms of social learning is an exciting area of research for all those interested in understanding the origin and the nature of animal learning in a social context. Moreover, imitation is an increasingly important research topic in Artificial Intelligence and social robotics which opens up the possibility of individualized social intelligence in robots that are part of a community, and allows us to harness not only individual learning by the single robot, but also the (...) acquisition of new skills by observing other members of the community. After an introduction to the main research issues in research on imitation in various fields, we motivate the particular focus of this work, namely the correspondence problem. We describe Action Learning for Imitation via Correspondences between Embodiments, an implemented generic framework for solving the correspondence problem between differently embodied robots. Alice enables a robotic agent to learn a behavioral repertoire suitable to performing a task by observing a model agent. Importantly, the model agent could possibly possess a different type of body, e.g. a different number of limbs or joints, a different height, different sensors, a different basic action repertoire, etc. Previously, in a test-bed where the agents differed according to their possible movement patterns, we demonstrated that the character of imitation achieved will depend on the granularity of subgoal matching, and on the metrics used to evaluate success. In our current work, we implemented Alice in a new test-bed called Rabit where simple simulated robotic arm agents use various metrics for evaluating success according to actions, states, effects, or weighted combinations. We examine the roles of synchronization, looseness of perceptual matching, and of proprioceptive matching by a series of experiments. Also, we study how Alice copes with changes in the embodiment of the imitator during learning. Our simulation results suggest that synchronization and loose perceptual matching allow for faster acquisition of behavioral compentencies at low error rates. Social learning plays a role as a replication mechanism for behaviors and results in variability when the transmitted behavior differs from the model’s behavior, thus providing the evolutionary substrate for culture and its pre-cursors. Social learning in robotics could therefore serve as the basis for culture in societies whose members include artificial agents. We address the use of imitative social learning mechanisms like Alice for transmission of skills between robots, and give first examples of transmission of a skill despite differences in embodiment of agents involved. In the particular setup, transmission occurs through a chain, as well as emerging in cyclic arrangements of robots. These simple examples demonstrate that by using social learning and imitation, cultural transmission is possible among robots, even in heterogeneous groups of robots. (shrink)

Adopting a functionalist perspective, we emphasize the interest of considering imitation as a single capacity with two functions: communication and learning. These two functions both imply such capacities as detection of novelty, attraction toward moving stimuli and perception-action coupling. We propose that the main difference between the processes involved in the two functions is that, in the case of learning, the dynamics is internal to the system constituted by an individual whereas in the case of communication, the dynamics concerns the (...) system composed by the perception of one individual coupled with the action of the other.In this paper, we compare the first developmental steps of imitation in three populations: typically developing children, children with autism, and robots. We show evidence of strong correlations between imitating and being imitated in typical infants and low-functioning children with autism. Relying on this evidence, the robotic perspective is to provide a generic architecture able not only to learn via imitation but also to interact as an emerging property of the system constituted by two similar architectures with a different history. (shrink)

"Intelligence" has long been considered to be a feature unique to human beings, giving us the capacity to imagine, to think, to deceive, to make complex connections between cause and effect, to devise elaborate stategies for solving problems. However, like all our other features, intelligence is a product of evolutionary change. Until recently, it was difficult to obtain evidence of this process from the frail testimony of a few bones and stone tools. It has become clear in the last 15 (...) years that the origins of human intelligence can be investigated by the comparative study of primates, our closest non-human relatives, giving strong impetus to the case for an "evolutionary psychology", the scientific study of the mind. (shrink)