Emergence of Locomotion Behaviours in Rich Environments

@article{Heess2017EmergenceOL,
  title={Emergence of Locomotion Behaviours in Rich Environments},
  author={Nicolas Heess and TB Dhruva and Srinivasan Sriram and Jay Lemmon and Josh Merel and Greg Wayne and Yuval Tassa and Tom Erez and Ziyu Wang and S. M. Ali Eslami and Martin A. Riedmiller and David Silver},
  journal={CoRR},
  year={2017},
  volume={abs/1707.02286}
}
The reinforcement learning paradigm allows, in principle, for complex behaviours to be learned directly from simple reward signals. In practice, however, it is common to carefully hand-design the reward function to encourage a particular solution, or to derive it from demonstration data. In this paper explore how a rich environment can help to promote the learning of complex behavior. Specifically, we train agents in diverse environmental contexts, and find that this encourages the emergence of… CONTINUE READING
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