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Inverse Game Theory

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

This week we read “Inverse Game Theory” by Volodymyr Kuleshov and Okke Schrijvers.

Inverse Game Theory (IGT) is basically Inverse Reinforcement Learning (IRL), but the demonstrations used for learning involve many different agents which cannot be isolated. That is, IGT tries to learn what the reward for each of the agents is, when they all play a Nash equilibrium. This should be useful for the value learning problem in the real world, where humans never act in isolation.

As usual, there will be free pizza. The first half hour is for stragglers to finish reading.

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This talk is part of the Engineering Safe AI series.

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