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No-regret Dynamics for Multi-agent Learning

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We review multi-agent learning, including equilibrium concepts such as Nash equilibrium and correlated equilibrium, as well as online-learning-based algorithms for computing them such as no-regret dynamics. These techniques were instrumental in the recent breakthrough of human-level performance in the board game Diplomacy by a computer.

Preparatory reading: Tim Roughgarden, Twenty Lectures on Algorithmic Game Theory, Ch. 17.

This talk is part of the Machine Learning Reading Group @ CUED series.

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