The effect of learning by imitation on a multi-robot system based on the coupling of low-level imitation strategy and online learning for cognitive map building

摘要

AbstractIt is assumed that future robots must coexist with human beings and behave as their companions. Consequently, the complexities of their tasks would increase. To cope with these complexities, scientists are inclined to adopt the anatomical functions of the brain for the mapping and the navigation in the field of robotics. While admitting the continuous works in improving the brain models and the cognitive mapping for robots' navigation, we show, in this paper, that learning by imitation leads to a positive effect not only in human behavior but also in the behavior of a multi-robot system. We present the interest of low-level imitation strategy at individual and social levels in the case of robots. Particularly, we show that adding a simple imitation capability to the brain model for building a cognitive map improves the ability of individual cognitive map building and boosts sharing information in an unknown environment. Taking into account the notion of imitative behavior, we also show that the individual discoveries (i.e. goals) could have an effect at the social level and therefore inducing the learning of new behaviors at the individual level. To analyze and validate our hypothesis, a series of experiments has been performed with and without a low-level imitation strategy in the multi-robot system.Keywords: learning by imitationimitationbio-inspired architecturecognitive mapmulti-robot system AcknowledgmentsThe authors would like to thank the financial support of the Tunisian General Direction of Scientific Research and Technological Renovation (DGRSRT) under the ARUB program 01/UR/11 02, the Institut Français de Tunisie, the INTERACT French project referenced ANR_09_CORD_014, the NEUROBOT french project referenced ANR-BLAN-SIMI2-L2-100617-13-01, and DIGITEO project AUTO EVAL.Notes1 The cognitive map is a graphical representation of the environment which is related to the perception of each robot. It allows the robot to navigate, to plan, and learn the important places in the environment.2 The robots were already learned the position of the two goals and created their cognitive map.