Éva Tardos 2026-11-05
Éva Tardos studies algorithms and the efficiency of systems in which participants act for themselves. Her work with Tim Roughgarden quantified inefficiency in selfish routing, relating equilibrium traffic to a centrally optimized flow.[ref][ref]
A small example shows the issue. Route one unit of traffic over two parallel links, one with latency when carrying flow and one with fixed latency one. The selfish equilibrium sends everything over the first link, giving total latency one: no user can improve by switching to the other link. Splitting traffic equally gives total latency , which minimizes . The equilibrium-to-optimum ratio is .
This is a precise price of anarchy calculation. It demonstrates why individually sensible choices can create avoidable aggregate delay and why a guarantee about an optimization algorithm does not automatically describe an uncoordinated network.
Figure 1.
Éva Tardos, portrait identified by the linked author, institutional or Commons source
.
Original FOCS 2000 paper, primary byline. Introduction and routing model: nonatomic routing, total latency and inefficiency bounds. This conference version is distinct from the later journal version.
Author-hosted paper dated 14 July 2015. Abstract and Introduction: smoothness arguments extend inefficiency bounds to broader equilibria and no-regret learning outcomes. Preliminary STOC version appeared in 2009; do not confuse manuscript date and first conference appearance.
Tim Roughgarden 2026-11-05
Tim Roughgarden studies the interaction between algorithms, economic incentives and computational limits. His work on selfish routing, including collaboration with Éva Tardos, asks how much efficiency is lost when network users minimize their own delays.[ref]
His Intrinsic Robustness of the Price of Anarchy by Tim Roughgarden develops a framework in which certain inefficiency bounds persist beyond a particular equilibrium description. The proof controls the aggregate cost of specified unilateral deviations, making the bound applicable to broader patterns of behavior such as appropriate learning outcomes.[ref]
This distinction is useful: proving that an optimal outcome exists, that an equilibrium exists and that observed adaptive behavior stays efficient are three different claims. A robustness argument states which behavioral conditions are actually sufficient for its guarantee. Columbia's institutional profile identifies algorithmic game theory and the design and limitations of algorithms as his research areas.[ref]
Figure 1.
Tim Roughgarden, portrait identified by the linked author, institutional or Commons source
.