Multi-method learning and assimilation

Abstract

Considering the wide range of possible behaviours to be acquired for domestic robots, applying a single learning method is clearly insufficient. In this paper, we propose a new strategy for behaviour acquisition for domestic robots where the behaviours are acquired using multiple differing learning methods that are subsequently incorporated into a common behaviour selection system, enabling them to be performed in appropriate situations. An example of the implementation of this strategy applied to the entertainment humanoid robot QRIO is introduced and the results are discussed.