Grounding communication in autonomous robots: An experimental study

This paper reports on experiments in which a physical autonomous robot is taught a basic vocabulary concerning objects in its close environment. Teaching is provided in one case by a second teacher robot and in another case by a human teacher. An imitative strategy, namely mutual following, is used to create a common perceptual context to learner and teacher agents, upon which the learner grounds its understanding of the teacher's words. Learning results from multiple associations between simultaneous and consecutive sensor stimuli and is performed by a Dynamical Recurrent Associative Memory Architecture. Successes and failures of the learning are investigated under different environmental constraints and by varying parameters internal to the agent's control system. The experiments are realised both in simulated and real environments. We observe correlations between environmental and internal parameters, namely that the duration of short-term memory of sensor stimuli has to be fixed in relation to the objects' relative dispersion and featural descriptions. We quantify our analysis by determining bounds on these parameters within which learning is successful.