Safe Exploration in Reinforcement Learning

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• Frances Ding (University of Cambridge)
• Wednesday 31 January 2018, 17:00-18:30
• Cambridge University Engineering Department, CBL Seminar room BE4-38. For directions see http://learning.eng.cam.ac.uk/Public/Directions.

If you have a question about this talk, please contact Adrià Garriga Alonso.

In reinforcement learning, the learning agent always faces a tradeoff between exploration and exploitation. Often, exploration is implemented as taking random actions, but in dangerous tasks, this can lead to highly negative rewards – damage to the agent or other parts of the environment. This week we discuss methods to minimize the risks in exploration and learn good policies both safely and efficiently.

Slides: https://valuealignment.ml/talks/2018-01-31-safe-exploration.pdf

This talk is part of the Engineering Safe AI series.

This talk is included in these lists:

• Cambridge University Engineering Department, CBL Seminar room BE4-38. For directions see http://learning.eng.cam.ac.uk/Public/Directions
• Cambridge talks
• Chris Davis' list
• Engineering Safe AI
• Trust & Technology Initiative - interesting events

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