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Prof
Google Deep Mind, University College London
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Schedule
Friday, June 12, 2020
2:00 PM Europe/London
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Recording provided by the organiser.
Domain
NeuroscienceHost
The Neurotheory Forum
Duration
70 minutes
Model-based approaches to control and decision making have long held the promise of being more powerful and data efficient than model-free counterparts. However, success with model-based methods has been limited to those cases where a perfect model can be queried. The game of Go was mastered by AlphaGo using a combination of neural networks and the MCTS planning algorithm. But planning required a perfect representation of the game rules. I will describe new algorithms that instead leverage deep neural networks to learn models of the environment which are then used to plan, and update policy and value functions. These new algorithms offer hints about how brains might approach planning and acting in complex environments.
Timothy Lillicrap
Prof
Google Deep Mind, University College London
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