Socially Guided XCS
Anis Najar, Olivier Sigaud, Mohamed Chétouani · 2015
In this paper, we show how we can improve task learning by using social interaction to guide the learning process of a robot, in a Human-Robot Interaction scenario. We introduce a novel method that simultaneously learns a social reward function on the teaching signals provided by a human and uses it to bootstrap task learning. We propose a model we call the Socially Guided XCS, based on the XCS framework, and we evaluate it in simulation with respect to the standard XCS algorithm. We show that our model improves the learning speed of XCS.