"The first decade of Algorithmic Mechanism Design (AMD) concentrated, very successfully, on the design of truthful mechanisms for the allocation of resources among agents with private preferences.Truthful mechanisms are ones that incentivize rational users to report their preferences truthfully.Truthfulness, however, for all its theoretical appeal, suffers from several inherent limitations, mainly its high communication and computation complexities.It is not surprising, therefore, that practical applications forego truthfulness and use simpler mechanisms instead.Simplicity in itself, however, is not sufficient, as any meaningful mechanism should also have some notion of fairness; otherwise agents will stop using it over time.In this project I plan to develop an innovative AMD theoretical framework that will go beyond truthfulness and focus instead on the natural themes of simplicity and fairness, in addition to computational tractability.One of my primary goals will be the design of simple and fair poly-time mechanisms that perform at near optimal levels with respect to important economic objectives such as social welfare and revenue.To this end, I will work toward providing precise definitions of simplicity and fairness and quantifying the effects of these restrictions on the performance levels that can be obtained.A major challenge in the evaluation of non-truthful mechanisms is defining a reasonable behavior model that will enable their evaluation.The success of this project could have a broad impact on Europe and beyond, as it would guide the design of natural mechanisms for markets of tens of billions of dollars in revenue, such as online advertising, or sales of wireless frequencies.The timing of this project is ideal, as the AMD field is now sufficiently mature to lead to a breakthrough and at the same time young enough to be receptive to new approaches and themes."