Monday, 15:45 - 16:10 h, Room: MA 043


Mingyu Guo
Computationally feasible automated mechanism design: General approach and a case study on budget-balanced and nearly efficient randomized mechanisms

Coauthors: Vincent Conitzer, Amy Greenwald, Nicholas Jennings, Victor Naroditskiy


In automated mechanism design, the idea is to computationally search through the space of feasible mechanisms, rather than to design them analytically by hand. Unfortunately, the most straightforward approach to automated mechanism design does not scale to large instances, because it requires searching over a very large space of possible functions. We describe an approach to automated mechanism design that is computationally feasible. Instead of optimizing over all feasible mechanisms, we carefully choose a parameterized subfamily of mechanisms. Then we optimize over mechanisms within this family, and analyze whether and to what extent the resulting mechanism is suboptimal outside the subfamily.
We demonstrate the usefulness of our approach with a case study on budget-balanced and nearly efficient mechanisms. Faltings [05] proposed the idea of excluding one agent uniformly at random from the decision and making him the residual claimant. We show that Faltings' mechanism can be generalized to a parameterized subfamily of mechanisms. In two example scenarios, by optimizing within the above subfamily, we are able to find mechanisms that are budget-balanced and nearly efficient.


Talk 2 of the invited session Mon.3.MA 043
"Design of optimal mechanisms" [...]
Cluster 8
"Game theory" [...]


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