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Learning and Efficiency of Outcomes in Games

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Tuesday 6th Jun 2017, 11.15am
Lecture Theatre 2, Mathematical Institute (University of Oxford) Andrew Wiles Building Radcliffe Observatory Quarter, Woodstock Road Oxford OX2 6GG

Selfish behaviour can often lead to suboptimal outcome for all participants, a phenomenon illustrated by many classical examples in game theory. Over the last decade we developed good understanding on how to quantify the impact of strategic user behaviour on the overall performance in many games (including traffi c routing as well as online auctions). In this talk we will focus on games where players use a form of learning that helps themadapt to the environment, and consider two closely related questions: What are broad classes of learning behaviours that guarantee that game outcomes converge to the quality guaranteed by the price of anarchy, and how fast is this convergence. Or asking these questions more broadly: what learning guarantees high social welfare in games, when the game or the population of players is dynamically changing.

Booking advised: https://www.eventbrite.co.uk/e/ada-lovelace-lecture-eva-tardos-departmen...