Computing exact solutions of consensus halving and the Borsuk-Ulam theorem

We study the problem of finding an exact solution to the consensus halving problem. While recent work has shown that the approximate version of this problem is PPA-complete, we show that the exact version is much harder. Specifically, finding a solution with $n$ cuts is FIXP-hard, and deciding whether there exists a solution with fewer than $n$ cuts is ETR-complete. We also give a QPTAS for the case where each agent's valuation is a polynomial. Along the way, we define a new complexity class BU, which captures all problems that can be reduced to solving an instance of the Borsuk-Ulam problem exactly. We show that FIXP $\subseteq$ BU $\subseteq$ TFETR and that LinearBU $=$ PPA, where LinearBU is the subclass of BU in which the Borsuk-Ulam instance is specified by a linear arithmetic circuit

In Congestion Games, Taxes Achieve Optimal Approximation

In this work, we consider the problem of minimising the social cost in atomic congestion games. For this problem, we provide tight computational lower bounds along with taxation mechanisms yielding polynomial time algorithms with optimal approximation. Perhaps surprisingly, our results show that indirect interventions, in the form of efficiently computed taxation mechanisms, yield the same performance achievable by the best polynomial time algorithm, even when the latter has full control over the agents' actions. It follows that no other tractable approach geared at incentivizing desirable system behavior can improve upon this result, regardless of whether it is based on taxations, coordination mechanisms, information provision, or any other principle. In short: Judiciously chosen taxes achieve optimal approximation. Three technical contributions underpin this conclusion. First, we show that computing the minimum social cost is NP-hard to approximate within a given factor depending solely on the admissible resource costs. Second, we design a tractable taxation mechanism whose efficiency (price of anarchy) matches this hardness factor, and thus is worst-case optimal. As these results extend to coarse correlated equilibria, any no-regret algorithm inherits the same performances, allowing us to devise polynomial time algorithms with optimal approximation

Essays in Mechanism Design and Contest Theory

This dissertation contains three essays. They offer contributions to the fields of mechanism design (Chapters 1 and 2) and contest theory (Chapter 3). Chapter 1, co-authored with Wade Hann-Caruthers, studies the problem of aggregating privately-held preferences for a facility to be located on a plane. We show that for a large class of social cost functions, the mechanism that locates the facility at the coordinate-wise median of the agent’s ideal points is quantitatively optimal (in the sense that it has the smallest worst-case approximation ratio) among all deterministic, anonymous, and incentive-compatible mechanisms. We also obtain bounds on the worst-case approximation ratio of the coordinate-wise median mechanism for an important subclass of social cost functions. Chapter 2, co-authored with Wade Hann-Caruthers, studies a principal-agent project selection problem with asymmetric information and demonstrates the value for the principal in inducing partial verifiability constraints, such as no-overselling, on the agent. We consider a setting where the principal has to choose one among a set of available projects but the relevant information, such as each project's profitability, is held by a self-interested agent who might also have its own preference over the projects. If the agent is unconstrained in its ability to manipulate its private information, the principal can do no better than randomly choosing a project. But if the agent cannot oversell any of the projects, maybe because it must support its claims with evidence, we show that a simple cutoff mechanism (agent's favorite project is chosen among those that meet a cutoff profit level and a default project) is optimal for the principal. We also find evidence in support of the well-known ally-principle which says that principal delegates more authority to an agent with more aligned preferences. Chapter 3 studies the effect of increasing the value of prizes and competitiveness of contests on the effort exerted by participants in an incomplete information environment. We identify two natural sufficient conditions on the distribution of abilities in the population under which the interventions have opposite effects on effort. We also discuss applications to the design of optimal contests in three different environments, including the design of grading contests. Assuming that the value of a grade is determined by the information it reveals about the agent's ability, we establish a link between the informativeness of a grading scheme and the effort induced by it.</p