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Vision-Based Imitation Learning in Heterogeneous Multi-Robot Systems: Varying Physiology and Skill
2012
International Journal of Automation and Smart Technology
Imitation learning enables a learner to improve its abilities by observing others. Most robotic imitation learning systems only learn from demonstrators that are similar physically and in terms of skill level. In order to employ imitation learning in a heterogeneous multi-agent environment, we must consider both differences in skill, and physical differences (physiology, size). This paper describes an approach to imitation learning from heterogeneous demonstrators, using global vision. It
doi:10.5875/ausmt.v2i2.111
fatcat:bjiehyih7rgwbnbckg47wcrski