Timothy Lillicrap
Director of Research at Google DeepMind and CIFAR program co-director; works on deep RL for control
- Director of Research, Google DeepMind1
- Program Co-Director, Learning in Machines & Brains, CIFAR1
Timothy Lillicrap is a Director of Research at Google DeepMind, which Lillicrap joined as a research scientist in 2014, and a Program Co-Director of CIFAR's Learning in Machines & Brains program. Lillicrap's research focuses on machine learning for optimal control and decision-making and on using these frameworks to understand how the brain learns. Lillicrap is first author of "Continuous control with deep reinforcement learning" (2015), which presents an actor-critic algorithm based on the deterministic policy gradient for continuous action spaces, and a co-author of the AlphaZero and A3C papers.1234
Work
Continuous control with deep reinforcement learning (external site: arxiv.org)Published research
First author of the 2015 paper presenting an actor-critic, model-free algorithm based on the deterministic policy gradient that operates over continuous action spaces.2
AlphaZero and A3C (external site: arxiv.org)Published research
Co-author of "Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm" (2017) and of "Asynchronous Methods for Deep Reinforcement Learning" (2016).34
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