Nature Communications (Oct 2021)

Embodied intelligence via learning and evolution

  • Agrim Gupta,
  • Silvio Savarese,
  • Surya Ganguli,
  • Li Fei-Fei

DOI
https://doi.org/10.1038/s41467-021-25874-z
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 12

Abstract

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The authors propose a new framework, deep evolutionary reinforcement learning, evolves agents with diverse morphologies to learn hard locomotion and manipulation tasks in complex environments, and reveals insights into relations between environmental physics, embodied intelligence, and the evolution of rapid learning.