A formula for Nash equilibria in monotone singleton congestion games

This paper provides a simple formula describing all Nash equilibria in symmetric monotone singleton congestion games. Our approach also yields a new and short proof establishing the existence of a Nash equilibrium in this kind of congestion games without invoking the potential function or the nite improvement property.Singleton congestion games, Nash equilibria, Potential function, Finite improvement property

Nonsymmetric singleton congestion games: case of two resources

In this note we study the existence of Nash equilibria in nonsymmetric finite congestion games, complementing the results obtained by Milchtaich on monotone-decreasing congestion games. More specifically, we examine the case of two resources and we propose a simple method describing all Nash equilibria in this kind of congestion games. Additionally, we give a new and short proof establishing the existence of a Nash equilibrium in this type of games without invoking the potential function or the finite improvement property.Singleton congestion games, Nash equilibria, Potential function, Finite improvement property

Strong Nash Equilibria in Games with the Lexicographical Improvement Property

We introduce a class of finite strategic games with the property that every deviation of a coalition of players that is profitable to each of its members strictly decreases the lexicographical order of a certain function defined on the set of strategy profiles. We call this property the Lexicographical Improvement Property (LIP) and show that it implies the existence of a generalized strong ordinal potential function. We use this characterization to derive existence, efficiency and fairness properties of strong Nash equilibria. We then study a class of games that generalizes congestion games with bottleneck objectives that we call bottleneck congestion games. We show that these games possess the LIP and thus the above mentioned properties. For bottleneck congestion games in networks, we identify cases in which the potential function associated with the LIP leads to polynomial time algorithms computing a strong Nash equilibrium. Finally, we investigate the LIP for infinite games. We show that the LIP does not imply the existence of a generalized strong ordinal potential, thus, the existence of SNE does not follow. Assuming that the function associated with the LIP is continuous, however, we prove existence of SNE. As a consequence, we prove that bottleneck congestion games with infinite strategy spaces and continuous cost functions possess a strong Nash equilibrium

Security in network games

Attacks on the Internet are characterized by several alarming trends: 1) increases in frequency; 2) increases in speed; and 3) increases in severity. Modern computer worms simply propagate too quickly for human detection. Since attacks are now occurring at a speed which prevents direct human intervention, there is a need to develop automated defenses. Since the financial, social and political stakes are so high, we need defenses which are provably good against worst case attacks and are not too costly to deploy. In this dissertation we present two approaches to tackle these problems. For the first part of the dissertation we consider a game between an alert and a worm over a large network. We show, for this game, that it is possible to design an algorithm for the alerts that can prevent any worm from infecting more than a vanishingly small fraction of the nodes with high probability. Critical to our result is designing a communication network for spreading the alerts that has high expansion. The expansion of the network is related to the gap between the 1st and 2nd eigenvalues of the adjacency matrix. Intuitively high expansion ensures redundant connectivity. We also present results simulating our algorithm on networks of size up to $2^{25}$. In the second part of this dissertation we consider the virus inoculation game which models the selfish behavior of the nodes involved. We present a technique for this game which makes it possible to achieve the \u27windfall of malice\u27 even without the actual presence of malicious players. We also show the limitations of this technique for congestion games that are known to have a windfall of malice

Strong and Correlated Strong Equilibria in Monotone Congestion Games

The study of congestion games is central to the interplay between computer science and game theory. However, most work in this context does not deal with possible deviations by coalitions of players, a significant issue one may wish to consider. In order to deal with this issue we study the existence of strong and correlated strong equilibria in monotone congestion games. Our study of strong equilibrium deals with monotone-increasing congestion games, complementing the results obtained by Holzman and Law-Yone on monotone-decreasing congestion games. We then present a study of correlated-strong equilibrium for both decreasing and increasing monotone congestion games. Document type: Part of book or chapter of boo

Coordination Games on Weighted Directed Graphs

We study strategic games on weighted directed graphs, where each player’s payoff is defined as the sum of the weights on the edges from players who chose the same strategy, augmented by a fixed nonnegative integer bonus for picking a given strategy. These games capture the idea of coordination in the absence of globally common strategies. We identify natural classes of graphs for which finite improvement or coalition-improvement paths of polynomial length always exist, and consequently a (pure) Nash equilibrium or a strong equilibrium can be found in polynomial time. The considered classes of graphs are typical in network topologies: simple cycles correspond to the token ring local area networks, whereas open chains of simple cycles correspond to multiple independent rings topology from the recommendation G.8032v2 on Ethernet ring protection switching. For simple cycles, these results are optimal in the sense that without the imposed conditions on the weights and bonuses, a Nash equilibrium may not even exist. Finally, we prove that determining the existence of a Nash equilibrium or of a strong equilibrium is NP-complete already for unweighted graphs, with no bonuses assumed. This implies that the same problems for polymatrix games are strongly NP-hard. </jats:p

Selfishness and Malice in Distributed Systems

Large-scale distributed systems are increasingly prevalent. Two issues can impact the performance of such systems: selfishness and malice. Selfish players can reduce social welfare of games, and malicious nodes can disrupt networks. In this dissertation, we provide algorithms to address both of these issues. One approach to ameliorating selfishness in large networks is the idea of a mediator. A mediator implements a correlated equilibrium when it proposes a strategy to each player privately such that the mediators proposal is the best interest for every player to follow. In this dissertation, we present a mediator that implements the best correlated equilibrium for an extended El Farol game. The extended El Farol game we consider has both positive and negative network effects. We study the degree to which this type of mediator can decrease the social cost. In particular, we give an exact characterization of Mediation Value (MV) and Enforcement Value (EV) for this game. MV measures the efficiency of our mediator compared to the best Nash equilibrium, and EV measures the efficiency of our mediator compared to the optimal social cost. This sort of exact characterization is uncommon for games with both kinds of network effects. An interesting outcome of our results is that both the MV and EV values can be unbounded for our game. Recent years have seen significant interest in designing networks that are self-healing in the sense that they can automatically recover from adversarial attacks. Previous work shows that it is possible for a network to automatically recover, even when an adversary repeatedly deletes nodes in the network. However, there have not yet been any algorithms that self-heal in the case where an adversary takes over nodes in the network. In this dissertation, we address this gap. In particular, we describe a communication network over n nodes that ensures the following properties, even when an adversary controls up to t ≤ (1/4 − ε)n nodes, for any constant ε \u3e 0. First, the network provides point-to-point communication with message cost and latency that are asymptotically optimal in an amortized sense. Second, the expected total number of message corruptions is O(t(log* n)^2), after which the adversarially controlled nodes are effectively quarantined so that they cause no more corruptions. In the problem of reliable multiparty computation (RMC), there are n parties, each with an individual input, and the parties want to jointly and reliably compute a function f over n inputs, assuming that it is not necessary to maintain the privacy of the inputs. The problem is complicated by the fact that an omniscient adversary controls a hidden fraction of the parties. We describe a self-healing algorithm for this problem. In particular, for a fixed function f, with n parties and m gates, we describe how to perform RMC repeatedly as the inputs to f change. Our algorithm maintains the following properties, even when an adversary controls up to t ≤ (1/4 − ε)n parties, for any constant ε \u3e 0. First, our algorithm performs each reliable computation with the following amortized resource costs: O(m + n log n) messages, O(m + n log n) computational operations, and O(\ell) latency, where \ell is the depth of the circuit that computes f. Second, the expected total number of corruptions is O(t(log* n)^2). Our empirical results show that the message cost reduces by up to a factor of 60 for communication and a factor of 65 for computation, compared to algorithms of no self-healing