Machines can learn by simply observing, without being told what to look for

Image shows the aggregation behavior that the robots should learn (final snapshot of an already aggregated system). Credit: Roderich Gross We have developed a new machine learning method at the University of Sheffield called Turing Learning that allows machines to model natural or artificial systems.In Turing Learning, a machine optimizes models of a system under investigation. The machine observes the system, without being told what to look for. This overcomes the limitation of conventional machine learning methods that optimize models according to predefined similarity metrics, such as the sum of square error to measure the difference between the output of the models and that of the system. For complex systems, such as swarms, defining a useful metric can be challenging. Moreover, an unsuitable metric may not distinguish well between good and…


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