The curse of ties in congestion games with limited lookahead

We introduce a novel framework to model limited lookahead in congestion games. Intuitively, the players enter the game sequentially and choose an optimal action under the assumption that the k - 1 subsequent players play subgame-perfectly. Our model naturally interpolates between outcomes of greedy best-response (k = 1) and subgame-perfect outcomes (k = n, the number of players). We study the impact of limited lookahead (parameterized by k) on the stability and inefficiency of the resulting outcomes. As our results reveal, increased lookahead does not necessarily lead to better outcomes; in fact, its effect crucially depends on the existence of ties and the type of game under consideration

Selfishness Level of Strategic Games

We introduce a new measure of the discrepancy in strategic games between the social welfare in a Nash equilibrium and in a social optimum, that we call selfishness level. It is the smallest fraction of the social welfare that needs to be added to the players' payoffs to ensure that a Nash equilibrium of the resulting game is also its social optimum. This notion is unrelated to that of price of stability. We compute the selfishness level for some selected games. In particular, the selfishness level of finite ordinal potential games is finite, while that of a Cournot competition oligopoly game and Tragedy of the Commons game is infinite. We also provide an estimate on the selfishness level of linear congestion games and fair cost sharing games

Generalized Incremental Mechanisms for Scheduling Games

We study the problem of devising truthful mechanisms for cooperative cost sharing games that realize (approximate) budget balance and social cost. Recent negative results show that group-strategyproof mechanisms can only achieve very poor approximation guarantees for several fundamental cost sharing games. Driven by these limitations, we consider cost sharing mechanisms that realize the weaker notion of weak groupstrategyproofness. Mehta et al. [Games and Economic Behavior, 67:125–155, 2009] recently introduced the broad class of weakly group-strategyproof acyclic mechanisms and show that several primal-dual approximation algorithms naturally give rise to such mechanisms with attractive approximation guarantees. In this paper, we provide a simple yet powerful approach that enables us to turn any r-approximation algorithm into a r-budget balanced acyclic mechanism. We demonstrate the applicability of our approach by deriving weakly group-strategyproof mechanisms for several fundamental scheduling problems that outperform the best possible approximation guarantees of Moulin mechanisms. The mechanisms that we develop for completion time scheduling problems are the first mechanisms that achieve constant budget balance and social cost approximation factors. Interestingly, our mechanisms belong to the class of generalized incremental mechanisms proposed by Moulin [Social Choice and Welfare, 16:279–320, 1999]

Cost sharing over combinatorial domains: Complement-free cost functions and beyond

We study mechanism design for combinatorial cost sharing models. Imagine that multiple items or services are available to be shared among a set of interested agents. The outcome of a mechanism in this setting consists of an assignment, determining for each item the set of players who are granted service, together with respective payments. Although there are several works studying specialized versions of such problems, there has been almost no progress for general combinatorial cost sharing domains until recently [7]. Still, many questions about the interplay between strategyproofness, cost recovery and economic efficiency remain unanswered. The main goal of our work is to further understand this interplay in terms of budget balance and social cost approximation. Towards this, we provide a refinement of cross-monotonicity (which we term trace-monotonicity) that is applicable to iterative mechanisms. The trace here refers to the order in which players become finalized. On top of this, we also provide two parameterizations (complementary to a certain extent) of cost functions which capture the behavior of their average cost-shares. Based on our trace-monotonicity property, we design a scheme of ascending cost sharing mechanisms which is applicable to the combinatorial cost sharing setting with symmetric submodular valuations. Using our first cost function parameterization, we identify conditions under which our mechanism is weakly group-strategyproof, O(1)-budget-balanced and O(Hn)-approximate with respect to the social cost. Further, we show that our mechanism is budget-balanced and Hn-approximate if both the valuations and the cost functions are symmetric submodular; given existing impossibility results, this is best possible. Finally, we consider general valuation functions and exploit our second parameterization to derive a more fine-grained analysis of the Sequential Mechanism introduced by Moulin. This mechanism is budget balanced by construction, but in general only guarantees a poor social cost approximation of n. We identify conditions under which the mechanism achieves improved social cost approximation guarantees. In particular, we derive improved mechanisms for fundamental cost sharing problems, including Vertex Cover and Set Cover

On fair cost facility location games with non-singleton players

In the fair cost facility location game, players control terminals and must open and connect each terminal to a facility, while paying connection costs and equally sharing the opening costs associated with the facilities it connects to. In most of the literature, it is assumed that each player control a single terminal. We explore a more general version of the game where each player may control multiple terminals. We prove that this game does not always possess pure Nash equilibria, and deciding whether an instance has equilibria is NP-Hard, even in metric instances. Furthermore, we present results regarding the efficiency of equilibria, showing that the price of stability of this game is equal to the price of anarchy, in both uncapacitated and capacitated settings

On the inefficiency of equilibria in linear bottleneck congestion games

We study the inefficiency of equilibrium outcomes in bottleneck congestion games. These games model situations in which strategic players compete for a limited number of facilities. Each player allocates his weight to a (feasible) subset of the facilities with the goal to minimize the maximum (weight-dependent) latency that he experiences on any of these facilities. We derive upper and (asymptotically) matching lower bounds on the (strong) price of anarchy of linear bottleneck congestion games for a natural load balancing social cost objective (i.e., minimize the maximum latency of a facility). We restrict our studies to linear latency functions. Linear bottleneck congestion games still constitute a rich class of games and generalize, for example, load balancing games with identical or uniformly related machines with or without restricted assignments

On the effectiveness of connection tolls in fair cost facility location games

We investigate the effectiveness of tolls to reduce the inefficiency of Nash equilibria in the classical fair cost facility location game. In this game, every terminal corresponds to a selfish player who wants to connect to some facility at minimum cost. The cost of a player is determined by the connection cost to the chosen facility plus an equal share of its opening cost. We are interested in the problem of imposing tolls on the connections to induce a socially optimal Nash equilibrium such that the total amount of tolls is minimized. It turns out that this problem is challenging to solve even for simple special cases. We provide polynomial-time algorithms for (i) instances with two facilities, and (ii) instances with a constant number of facilities arranged as a star. Our algorithm for (ii) exploits a relation between our tolling problem and a novel bipartite matching problem without crossings, which we prove to be NP-hard

The Traveling k-Median Problem: Approximating optimal network coverage

We introduce the Traveling k-Median Problem (TkMP) as a natural extension of the k-Median Problem, where k agents (medians) can move through a graph of n nodes over a discrete time horizon of ω steps. The agents start and end at designated nodes, and in each step can hop to an adjacent node to improve coverage. At each time step, we evaluate the coverage cost as the total connection cost of each node to its closest median. Our goal is to minimize the sum of the coverage costs over the entire time horizon. In this paper, we initiate the study of this problem by focusing on the uniform case, i.e., when all edge costs are uniform and all agents share the same start and end locations. We show that this problem is NP-hard in general and can be solved optimally in time O(ω2n2 k). We obtain a 5-approximation algorithm if the number of agents is large (i.e., k≥ n/ 2 ). The more challenging case emerges if the number of agents is small (i.e., k< n/ 2 ). Our main contribution is a novel rounding scheme that allows us to round an (approximate) solution to the ‘continuous movement’ relaxation of the problem to a discrete one (incurring a bounded loss). Using our scheme, we derive constant-factor approximation algorithms on path and cycle graphs. For general graphs, we use a different (more direct) approach and derive an O(min{ω,n}) -approximation algorithm if d(s,t)≤2ω, and an O(d(s,t)+ω) -approximation algorithm if d(s,t)>2ω, where d(s, t) is the distance between the start and end point