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The Interplay of Machine Learning and Mechanism Design

The Interplay of Machine Learning and Mechanism Design

This video was recorded at 24th Annual Conference on Neural Information Processing Systems (NIPS), Vancouver 2010. In the economic theory of mechanism design, the goal is to elicit private information from each of multiple agents in order to select a desirable system wide outcome, and despite agent self-interest in promoting individually beneficial outcomes. Auctions provide a canonical example, with information elicited in the form of bids, and an allocation of resources and payments defining an outcome. Indeed, one aspect of the emerging interplay between machine learning (ML) and mechanism design (MD) arises by interpreting auctions as a method for learning agent valuation functions. In addition to seeking sufficient accuracy to support optimal resource allocation, we require for... Show More
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