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Autonomous task sequencing in a robot swarm.

Lorenzo GarattoniMauro Birattari
Published in: Science robotics (2021)
Robot swarms mimic natural systems in which collective abilities emerge from the interaction of individuals. So far, the swarm robotics literature has focused on the emergence of mechanical abilities (e.g., push a heavy object) and simple cognitive abilities (e.g., select a path between two alternatives). In this article, we present a robot swarm in which a complex cognitive ability emerged. This swarm was able to collectively sequence tasks whose order of execution was a priori unknown. Because sequencing tasks is an albeit simple form of planning, the robot swarm that we present provides a different perspective on a pivotal debate in the history of artificial intelligence: the debate on planning in robotics. In the proposed swarm, the two robotics paradigms-deliberative (sense-model-plan-act) and reactive (sense-act)-that are traditionally considered antithetical coexist in a particular way: The ability to plan emerges at the collective level from the interaction of reactive individuals.
Keyphrases
  • artificial intelligence
  • working memory
  • machine learning
  • big data
  • deep learning
  • systematic review