Grounding of Robots Behaviors
Louis Hugues, Alexis Drogoul · 2001
This paper addresses the problem of learning robot be-haviors in real environments. Robot behaviors have not only to be grounded in the physical world but also in the human space where they are suppose to take place. The paper briefly presents a learning model relying on teaching by demonstrations, enabling the user to trans-mit its intentions during real experiments. Important properties are outlined and the probabilistic learning process is described. Finally, we indicate how grounded behavior could be interfaced to a symbolic level.