Effect of a Low Level Imitation Strategy on an Autonomous Multi-Robot System Using On-Line Learning for Cognitive Map Building

In this paper, we present the interest of low level imitation strategy on individual and population levels in the field of Multi-Robot System. Particularly, we show that adding a simple imitation capability to our bio-inspired architecture boosts the ability of individual cognitive map building. Taking into account the notion of imitative behavior, we also show that the individual discoveries in each robot (i.e. goals) could have an effect on population level and therfore it induces a new learning capability at the individual level. To analyze and validate our hypothesis, a series of experiments have been performed with and without a low level imitation strategy.