https://www.cs.drexel.edu/~vg399/

AG 1   Info

AG Audience

English

60 Minutes

Saarbrücken

This talk will introduce the model of “learning-augmented mechanism design” (or “mechanism design with predictions”), which is an alternative model for the design and analysis of mechanisms in settings that involve strategic and self-interested agents. Aiming to complement the traditional approach in computer science, which analyzes the performance of algorithms based on worst-case instances, recent work on “algorithms with predictions” has developed algorithms that are enhanced with machine-learned predictions regarding the optimal solution. The algorithms can use this information to guide their decisions and the goal is to achieve much stronger performance guarantees when these predictions are accurate (consistency) while also maintaining good worst-case guarantees, even if these predictions are very inaccurate (robustness). This talk will focus on the adaptation of this framework into mechanism design and focus on mechanisms that leverage such unreliable predictions to achieve improved outcomes in settings involving strategic agents

Nidhi Rathi

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