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3 papers

2017arXiv preprint arXiv:1707.02286 (presented at NeurIPS 2017)

Emergence of Locomotion Behaviours in Rich Environments

Jay Lemay, David Silver, Nicolas Heess, Srinivasan Sriram, Darren King, Koray Kavukcuoglu

Finding: The trained policies exhibited emergent behaviors like walking, running, jumping, and even leaping across various environments, demonstrating robust locomotion.

locomotion deep reinforcement learning

2015Nature, vol. 518, no. 7540, pp. 529-533, DOI: 10.1038/nature14236

Human-level control through deep reinforcement learning

Diederik Kingma, Ioannis Antonoglou, Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Martin Riedmiller, Alex Graves

Finding: DQN achieved human-level or better performance on 49 Atari games, marking the first major success of Deep RL.

DQN deep reinforcement learning

1988Machine Learning, vol. 3, no. 1, pp. 9-44, DOI: 10.1007/BF00115009

Learning to predict by the methods of temporal differences

Richard S. Sutton

Finding: TD methods were shown to converge faster than Monte Carlo methods in prediction problems and became a cornerstone of modern RL.

reinforcement learning temporal difference