IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures

[joyhuang9473]

IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures

• Author: Lasse Espeholt, Hubert Soyer, Remi Munos, Karen Simonyan, Volodymir Mnih, Tom Ward, Yotam Doron, Vlad Firoiu, Tim Harley, Iain Dunning, Shane Legg, Koray Kavukcuoglu
• Origin: https://arxiv.org/abs/1802.01561
• Related:
  • https://github.com/deepmind/scalable_agent

[joyhuang9473]

@wassname

IMPALA is an agent that played all atari games at once and managed to get an average of 60% of human performance. Normally a differen't agent is trained for each game, so this one is unique, and it's weight may allow transfer learning more than is normal in RL