Table of Contents

Volume 521 Number 7553 pp394-556

28 May 2015

About the cover

A robot with a broken front-right leg. To keep walking despite that damage, it executes an ‘Intelligent Trial and Error’ algorithm that conducts experiments based on previous (simulated) experience to find a behaviour that still works. Autonomous mobile robots would be extremely useful in remote or hostile environments such as space, deep oceans or disaster areas. An outstanding challenge is to make such robots able to recover after damage. Jean-Baptiste Mouret and colleagues have developed a machine learning algorithm that enables damaged robots to quickly regain their ability to perform tasks. When they sustain damage — such as broken or even missing legs — the robots adopt an intelligent trial-and-error approach, trying out possible behaviours that they calculate to be potentially high-performing. After a handful of such experiments they discover, in less than two minutes, a compensatory behaviour that works in spite of the damage. Cover Antoine Cully/ Pierre & Marie Curie University. Inset: Alexander Vail

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