TY - CONF AU - Polevoy, Gleb AU - de Weerdt, M.M. AU - Jonker, C.M. ID - 17655 KW - agents KW - action KW - repeated reciprocation KW - fixed KW - floating KW - network KW - Nash equilibrium KW - social welfare KW - price of anarchy KW - price of stability KW - convex combination T2 - Proceedings of the 2016 European Conference on Artificial Intelligence TI - The Game of Reciprocation Habits VL - Volume 285: ECAI 2016 ER - TY - CONF AU - Polevoy, Gleb AU - de Weerdt, Mathijs AU - Jonker, Catholijn ID - 17656 KW - agent's influence KW - behavior KW - convergence KW - perron-frobenius KW - reciprocal interaction KW - repeated reciprocation SN - 978-1-4503-4239-1 T2 - Proceedings of the 2016 International Conference on Autonomous Agents and Multiagent Systems TI - The Convergence of Reciprocation ER - TY - CONF AB - We study a new class of games which generalizes congestion games and its bottleneck variant. We introduce congestion games with mixed objectives to model network scenarios in which players seek to optimize for latency and bandwidths alike. We characterize the existence of pure Nash equilibria (PNE) and the convergence of improvement dynamics. For games that do not possess PNE we give bounds on the approximation ratio of approximate pure Nash equilibria. AU - Feldotto, Matthias AU - Leder, Lennart AU - Skopalik, Alexander ID - 209 T2 - Proceedings of the 10th Annual International Conference on Combinatorial Optimization and Applications (COCOA) TI - Congestion Games with Mixed Objectives ER - TY - GEN AU - Handirk, Tobias ID - 1082 TI - Über die Rolle von Informationen in Verkehrsnetzwerken ER - TY - JOUR AB - Abstract—Max-min fairness (MMF) is a widely known approachto a fair allocation of bandwidth to each of the usersin a network. This allocation can be computed by uniformlyraising the bandwidths of all users without violating capacityconstraints. We consider an extension of these allocations byraising the bandwidth with arbitrary and not necessarily uniformtime-depending velocities (allocation rates). These allocationsare used in a game-theoretic context for routing choices, whichwe formalize in progressive filling games (PFGs). We present avariety of results for equilibria in PFGs. We show that these gamespossess pure Nash and strong equilibria. While computation ingeneral is NP-hard, there are polynomial-time algorithms forprominent classes of Max-Min-Fair Games (MMFG), includingthe case when all users have the same source-destination pair.We characterize prices of anarchy and stability for pure Nashand strong equilibria in PFGs and MMFGs when players havedifferent or the same source-destination pairs. In addition, weshow that when a designer can adjust allocation rates, it is possibleto design games with optimal strong equilibria. Some initial resultson polynomial-time algorithms in this direction are also derived. AU - Harks, Tobias AU - Höfer, Martin AU - Schewior, Kevin AU - Skopalik, Alexander ID - 159 IS - 4 JF - IEEE/ACM Transactions on Networking TI - Routing Games With Progressive Filling ER - TY - CONF AB - In this paper we consider a strategic variant of the online facility location problem. Given is a graph in which each node serves two roles: it is a strategic client stating requests as well as a potential location for a facility. In each time step one client states a request which induces private costs equal to the distance to the closest facility. Before serving, the clients may collectively decide to open new facilities, sharing the corresponding price. Instead of optimizing the global costs, each client acts selfishly. The prices of new facilities vary between nodes and also change over time, but are always bounded by some fixed value α. Both the requests as well as the facility prices are given by an online sequence and are not known in advance.We characterize the optimal strategies of the clients and analyze their overall performance in comparison to a centralized offline solution. If all players optimize their own competitiveness, the global performance of the system is O(√α⋅α) times worse than the offline optimum. A restriction to a natural subclass of strategies improves this result to O(α). We also show that for fixed facility costs, we can find strategies such that this bound further improves to O(√α). AU - Drees, Maximilian AU - Feldkord, Björn AU - Skopalik, Alexander ID - 149 T2 - Proceedings of the 10th Annual International Conference on Combinatorial Optimization and Applications (COCOA) TI - Strategic Online Facility Location ER - TY - JOUR AB - Comparative evaluations of peer-to-peer protocols through simulations are a viable approach to judge the performance and costs of the individual protocols in large-scale networks. In order to support this work, we present the peer-to-peer system simulator PeerfactSim.KOM, which we extended over the last years. PeerfactSim.KOM comes with an extensive layer model to support various facets and protocols of peer-to-peer networking. In this article, we describe PeerfactSim.KOM and show how it can be used for detailed measurements of large-scale peer-to-peer networks. We enhanced PeerfactSim.KOM with a fine-grained analyzer concept, with exhaustive automated measurements and gnuplot generators as well as a coordination control to evaluate sets of experiment setups in parallel. Thus, by configuring all experiments and protocols only once and starting the simulator, all desired measurements are performed, analyzed, evaluated, and combined, resulting in a holistic environment for the comparative evaluation of peer-to-peer systems. An immediate comparison of different configurations and overlays under different aspects is possible directly after the execution without any manual post-processing. AU - Feldotto, Matthias AU - Graffi, Kalman ID - 145 IS - 5 JF - Concurrency and Computation: Practice and Experience TI - Systematic evaluation of peer-to-peer systems using PeerfactSim.KOM VL - 28 ER - TY - GEN AU - Pfannschmidt, Karlson ID - 251 TI - Solving the aggregated bandits problem ER - TY - JOUR AB - We consider structural and algorithmic questions related to the Nash dynamics of weighted congestion games. In weighted congestion games with linear latency functions, the existence of pure Nash equilibria is guaranteed by a potential function argument. Unfortunately, this proof of existence is inefficient and computing pure Nash equilibria in such games is a PLS-hard problem even when all players have unit weights. The situation gets worse when superlinear (e.g., quadratic) latency functions come into play; in this case, the Nash dynamics of the game may contain cycles and pure Nash equilibria may not even exist. Given these obstacles, we consider approximate pure Nash equilibria as alternative solution concepts. A ρ--approximate pure Nash equilibrium is a state of a (weighted congestion) game from which no player has any incentive to deviate in order to improve her cost by a multiplicative factor higher than ρ. Do such equilibria exist for small values of ρ? And if so, can we compute them efficiently?We provide positive answers to both questions for weighted congestion games with polynomial latency functions by exploiting an “approximation” of such games by a new class of potential games that we call Ψ-games. This allows us to show that these games have d!-approximate pure Nash equilibria, where d is the maximum degree of the latency functions. Our main technical contribution is an efficient algorithm for computing O(1)-approximate pure Nash equilibria when d is a constant. For games with linear latency functions, the approximation guarantee is 3+√5/2 + Oγ for arbitrarily small γ > 0; for latency functions with maximum degree d≥ 2, it is d2d+o(d). The running time is polynomial in the number of bits in the representation of the game and 1/γ. As a byproduct of our techniques, we also show the following interesting structural statement for weighted congestion games with polynomial latency functions of maximum degree d ≥ 2: polynomially-long sequences of best-response moves from any initial state to a dO(d2)-approximate pure Nash equilibrium exist and can be efficiently identified in such games as long as d is a constant.To the best of our knowledge, these are the first positive algorithmic results for approximate pure Nash equilibria in weighted congestion games. Our techniques significantly extend our recent work on unweighted congestion games through the use of Ψ-games. The concept of approximating nonpotential games by potential ones is interesting in itself and might have further applications. AU - Caragiannis, Ioannis AU - Fanelli, Angelo AU - Gravin, Nick AU - Skopalik, Alexander ID - 320 IS - 1 JF - Transactions on Economics and Computation TI - Approximate Pure Nash Equilibria in Weighted Congestion Games: Existence, Efficient Computation, and Structure VL - 3 ER - TY - GEN AU - Pautz, Jannis ID - 316 TI - Budget Games with priced strategies ER - TY - CONF AB - In \emph{bandwidth allocation games} (BAGs), the strategy of a player consists of various demands on different resources. The player's utility is at most the sum of these demands, provided they are fully satisfied. Every resource has a limited capacity and if it is exceeded by the total demand, it has to be split between the players. Since these games generally do not have pure Nash equilibria, we consider approximate pure Nash equilibria, in which no player can improve her utility by more than some fixed factor $\alpha$ through unilateral strategy changes. There is a threshold $\alpha_\delta$ (where $\delta$ is a parameter that limits the demand of each player on a specific resource) such that $\alpha$-approximate pure Nash equilibria always exist for $\alpha \geq \alpha_\delta$, but not for $\alpha < \alpha_\delta$. We give both upper and lower bounds on this threshold $\alpha_\delta$ and show that the corresponding decision problem is ${\sf NP}$-hard. We also show that the $\alpha$-approximate price of anarchy for BAGs is $\alpha+1$. For a restricted version of the game, where demands of players only differ slightly from each other (e.g. symmetric games), we show that approximate Nash equilibria can be reached (and thus also be computed) in polynomial time using the best-response dynamic. Finally, we show that a broader class of utility-maximization games (which includes BAGs) converges quickly towards states whose social welfare is close to the optimum. AU - Drees, Maximilian AU - Feldotto, Matthias AU - Riechers, Sören AU - Skopalik, Alexander ID - 271 T2 - Proceedings of the 8th International Symposium on Algorithmic Game Theory (SAGT) TI - On Existence and Properties of Approximate Pure Nash Equilibria in Bandwidth Allocation Games ER - TY - GEN AU - Kothe, Nils ID - 277 TI - Multilevel Netzwerk Spiele mit konstanten Entfernungen im Highspeed-Netzwerk ER - TY - JOUR AB - Inter-datacenter transfers of non-interactive but timely large flows over a private (managed) network is an important problem faced by many cloud service providers. The considered flows are non-interactive because they do not explicitly target the end users. However, most of them must be performed on a timely basis and are associated with a deadline. We propose to schedule these flows by a centralized controller, which determines when to transmit each flow and which path to use. Two scheduling models are presented in this paper. In the first, the controller also determines the rate of each flow, while in the second bandwidth is assigned by the network according to the TCP rules. We develop scheduling algorithms for both models and compare their complexity and performance. AU - Cohen, R. AU - Polevoy, Gleb ID - 17657 IS - 99 JF - Cloud Computing, IEEE Transactions on KW - Approximation algorithms KW - Approximation methods KW - Bandwidth KW - Cloud computing KW - Routing KW - Schedules KW - Scheduling SN - 2168-7161 TI - Inter-Datacenter Scheduling of Large Data Flows VL - PP ER - TY - JOUR AB - Abstract We study the problem of bandwidth allocation with multiple interferences. In this problem the input consists of a set of users and a set of base stations. Each user has a list of requests, each consisting of a base station, a frequency demand, and a profit that may be gained by scheduling this request. The goal is to find a maximum profit set of user requests S that satisfies the following conditions: (i) S contains at most one request per user, (ii) the frequency sets allotted to requests in S that correspond to the same base station are pairwise non-intersecting, and (iii) the QoS received by any user at any frequency is reasonable according to an interference model. In this paper we consider two variants of bandwidth allocation with multiple interferences. In the first each request specifies a demand that can be satisfied by any subset of frequencies that is large enough. In the second each request specifies a specific frequency interval. Furthermore, we consider two interference models, multiplicative and additive. We show that these problems are extremely hard to approximate if the interferences depend on both the interfered and the interfering base stations. On the other hand, we provide constant factor approximation algorithms for both variants of bandwidth allocation with multiple interferences for the case where the interferences depend only on the interfering base stations. We also consider a restrictive special case that is closely related to the Knapsack problem. We show that this special case is NP-hard and that it admits an FPTAS. AU - Bar-Yehuda, Reuven AU - Polevoy, Gleb AU - Rawitz, Dror ID - 17658 JF - Discrete Applied Mathematics KW - Local ratio SN - 0166-218X TI - Bandwidth allocation in cellular networks with multiple interferences VL - 194 ER - TY - CONF AB - Max-min fairness (MMF) is a widely known approach to a fair allocation of bandwidth to each of the users in a network. This allocation can be computed by uniformly raising the bandwidths of all users without violating capacity constraints. We consider an extension of these allocations by raising the bandwidth with arbitrary and not necessarily uniform time-depending velocities (allocation rates). These allocations are used in a game-theoretic context for routing choices, which we formalize in progressive filling games (PFGs).We present a variety of results for equilibria in PFGs. We show that these games possess pure Nash and strong equilibria. While computation in general is NP-hard, there are polynomial-time algorithms for prominent classes of Max-Min-Fair Games (MMFG), including the case when all users have the same source-destination pair. We characterize prices of anarchy and stability for pure Nash and strong equilibria in PFGs and MMFGs when players have different or the same source-destination pairs. In addition, we show that when a designer can adjust allocation rates, it is possible to design games with optimal strong equilibria. Some initial results on polynomial-time algorithms in this direction are also derived. AU - Harks, Tobias AU - Höfer, Martin AU - Schewior, Kevin AU - Skopalik, Alexander ID - 370 T2 - Proceedings of the 33rd Annual IEEE International Conference on Computer Communications (INFOCOM'14) TI - Routing Games with Progressive Filling ER - TY - GEN AU - Pahl, David ID - 373 TI - Reputationssysteme für zusammengesetzte Dienstleistungen ER - TY - CONF AU - Polevoy, Gleb AU - Trajanovski, Stojan AU - de Weerdt, Mathijs M. ID - 17659 KW - competition KW - equilibrium KW - market KW - models KW - shared effort games KW - simulation SN - 978-1-4503-2738-1 T2 - Proceedings of the 2014 International Conference on Autonomous Agents and Multi-agent Systems TI - Nash Equilibria in Shared Effort Games ER - TY - CONF AU - Polevoy, Gleb AU - de Weerdt, Mathijs M. ID - 17660 KW - dynamics KW - emotion modeling KW - negotiation KW - network interaction KW - shared effort game SN - 978-1-4503-2738-1 T2 - Proceedings of the 2014 International Conference on Autonomous Agents and Multi-agent Systems TI - Improving Human Interaction in Crowdsensing ER - TY - CONF AU - King, Thomas C. AU - Liu, Qingzhi AU - Polevoy, Gleb AU - de Weerdt, Mathijs AU - Dignum, Virginia AU - van Riemsdijk, M. Birna AU - Warnier, Martijn ID - 17661 KW - crowd-sensing KW - crowdsourcing KW - data aggregation KW - game theory KW - norms KW - reciprocation KW - self interested agents KW - simulation SN - 978-1-4503-2738-1 T2 - Proceedings of the 2014 International Conference on Autonomous Agents and Multi-agent Systems TI - Request Driven Social Sensing ER - TY - JOUR AU - Polevoy, Gleb AU - Smorodinsky, Rann AU - Tennenholtz, Moshe ID - 17662 IS - 1 JF - ACM Trans. Econ. Comput. KW - Competition KW - efficiency KW - equilibrium KW - market KW - social welfare SN - 2167-8375 TI - Signaling Competition and Social Welfare VL - 2 ER -