@inproceedings{17667,
abstract = {{Resolving distributed attacks benefits from collaboration between networks. We present three approaches for the same multi-domain defensive action that can be applied in such an alliance: 1) Counteract Everywhere, 2) Minimize Countermeasures, and 3) Minimize Propagation. First, we provide a formula to compute efficiency of a defense; then we use this formula to compute the efficiency of the approaches under various circumstances. Finally, we discuss how task execution order and timing influence defense efficiency. Our results show that the Minimize Propagation approach is the most efficient method when defending against the chosen attack.}},
author = {{Koning, Ralph and Polevoy, Gleb and Meijer, Lydia and de Laat, Cees and Grosso, Paola}},
booktitle = {{2019 6th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/ 2019 5th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom)}},
issn = {{null}},
keywords = {{computer network security, multinetwork environments, multidomain defensive action, task execution order, timing influence defense efficiency, distributed attacks, collaborative security defence approach, minimize propagation approach, minimize countermeasure approach, counteract everywhere approach, Conferences, Cloud computing, Computer crime, Edge computing, Security, Defense Approaches, Multi-Domain Defense, Collaborative Defense, Defense Algorithms, Computer Networks}},
pages = {{113--123}},
title = {{{Approaches for Collaborative Security Defences in Multi Network Environments}}},
doi = {{10.1109/CSCloud/EdgeCom.2019.000-9}},
year = {{2019}},
}
@phdthesis{8080,
abstract = {{This thesis investigates approximate pure Nash equilibria in different game-theoretic models. In such an outcome, no player can improve her objective by more than a given factor through a deviation to another strategy. In the first part, we investigate two variants of Congestion Games in which the existence of pure Nash equilibria is guaranteed through a potential function argument. However, the computation of such equilibria might be hard. We construct and analyze approximation algorithms that enable the computation of states with low approximation factors in polynomial time. To show their guarantees we use sub games among players, bound the potential function values of arbitrary states and exploit a connection between Shapley and proportional cost shares. Furthermore, we apply and analyze sampling techniques for the computation of approximate Shapley values in different settings. In the second part, we concentrate on the existence of approximate pure Nash equilibria in games in which no pure Nash equilibria exist in general. In the model of Coevolving Opinion Formation Games, we bound the approximation guarantees for natural states nearly independent of the specific definition of the players' neighborhoods by applying a concept of virtual costs. For the special case of only one influential neighbor, we even show lower approximation factors for a natural strategy. Then, we investigate a two-sided Facility Location Game among facilities and clients on a line with an objective function consisting of distance and load. We show tight bounds on the approximation factor for settings with three facilities and infinitely many clients. For the general scenario with an arbitrary number of facilities, we bound the approximation factor for two promising candidates, namely facilities that are uniformly distributed and which are paired.}},
author = {{Feldotto, Matthias}},
title = {{{Approximate Pure Nash Equilibria in Congestion, Opinion Formation and Facility Location Games}}},
doi = {{10.17619/UNIPB/1-588}},
year = {{2019}},
}
@inproceedings{5471,
abstract = {{We characterise the set of dominant strategy incentive compatible (DSIC), strongly budget balanced (SBB), and ex-post individually rational (IR) mechanisms for the multi-unit bilateral trade setting. In such a setting there is a single buyer and a single seller who holds a finite number k of identical items. The mechanism has to decide how many units of the item are transferred from the seller to the buyer and how much money is transferred from the buyer to the seller. We consider two classes of valuation functions for the buyer and seller: Valuations that are increasing in the number of units in possession, and the more specific class of valuations that are increasing and submodular.
Furthermore, we present some approximation results about the performance of certain such mechanisms, in terms of social welfare: For increasing submodular valuation functions, we show the existence of a deterministic 2-approximation mechanism and a randomised e/(1-e) approximation mechanism, matching the best known bounds for the single-item setting.}},
author = {{Lazos, Philip and Goldberg, Paul and Skopalik, Alexander and Gerstgrasser, Matthias and de Keijzer, Bart}},
booktitle = {{Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI)}},
location = {{Honolulu, Hawaii, USA}},
title = {{{ Multi-unit Bilateral Trade}}},
doi = {{10.1609/aaai.v33i01.33011973}},
year = {{2019}},
}
@inproceedings{10281,
abstract = {{Competing firms tend to select similar locations for their stores. This phenomenon, called the principle of minimum differentiation, was captured by Hotelling with a landmark model of spatial competition but is still the object of an ongoing scientific debate. Although consistently observed in practice, many more realistic variants of Hotelling's model fail to support minimum differentiation or do not have pure equilibria at all. In particular, it was recently proven for a generalized model which incorporates negative network externalities and which contains Hotelling's model and classical selfish load balancing as special cases, that the unique equilibria do not adhere to minimum differentiation. Furthermore, it was shown that for a significant parameter range pure equilibria do not exist. We derive a sharp contrast to these previous results by investigating Hotelling's model with negative network externalities from an entirely new angle: approximate pure subgame perfect equilibria. This approach allows us to prove analytically and via agent-based simulations that approximate equilibria having good approximation guarantees and that adhere to minimum differentiation exist for the full parameter range of the model. Moreover, we show that the obtained approximate equilibria have high social welfare.}},
author = {{Feldotto, Matthias and Lenzner, Pascal and Molitor, Louise and Skopalik, Alexander}},
booktitle = {{Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems}},
location = {{Montreal QC, Canada}},
pages = {{1949----1951}},
publisher = {{International Foundation for Autonomous Agents and Multiagent Systems}},
title = {{{ From Hotelling to Load Balancing: Approximation and the Principle of Minimum Differentiation}}},
year = {{2019}},
}
@inproceedings{2484,
abstract = {{We study the classic bin packing problem in a fully-dynamic setting, where new items can arrive and old items may depart. We want algorithms with low asymptotic competitive ratio while repacking items sparingly between updates. Formally, each item i has a movement cost c_i >= 0, and we want to use alpha * OPT bins and incur a movement cost gamma * c_i, either in the worst case, or in an amortized sense, for alpha, gamma as small as possible. We call gamma the recourse of the algorithm. This is motivated by cloud storage applications, where fully-dynamic bin packing models the problem of data backup to minimize the number of disks used, as well as communication incurred in moving file backups between disks. Since the set of files changes over time, we could recompute a solution periodically from scratch, but this would give a high number of disk rewrites, incurring a high energy cost and possible wear and tear of the disks. In this work, we present optimal tradeoffs between number of bins used and number of items repacked, as well as natural extensions of the latter measure.}},
author = {{Feldkord, Björn and Feldotto, Matthias and Gupta, Anupam and Guruganesh, Guru and Kumar, Amit and Riechers, Sören and Wajc, David}},
booktitle = {{45th International Colloquium on Automata, Languages, and Programming (ICALP 2018)}},
editor = {{Chatzigiannakis, Ioannis and Kaklamanis, Christos and Marx, Dániel and Sannella, Donald}},
isbn = {{978-3-95977-076-7}},
issn = {{1868-8969}},
location = {{Prag}},
pages = {{51:1--51:24}},
publisher = {{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik}},
title = {{{Fully-Dynamic Bin Packing with Little Repacking}}},
doi = {{10.4230/LIPIcs.ICALP.2018.51}},
volume = {{107}},
year = {{2018}},
}
@inproceedings{2831,
abstract = {{We consider a market where final products or services are compositions of a number of basic services. Users are asked to evaluate the quality of the composed product after purchase. The quality of the basic service influences the performance of the composed services but cannot be observed directly. The question we pose is whether it is possible to use user evaluations on composed services to assess the quality of basic services. We discuss how to combine aggregation of evaluations across users and disaggregation of information on composed services to derive valuations for the single components. As a solution we propose to use the (weighted) average as aggregation device in connection with the Shapley value as disaggregation method, since this combination fulfills natural requirements in our context. In addition, we address some occurring computational issues: We give an approximate solution concept using only a limited number of evaluations which guarantees nearly optimal results with reduced running time. Lastly, we show that a slightly modified Shapley value and the weighted average are still applicable if the evaluation profiles are incomplete.}},
author = {{Feldotto, Matthias and Haake, Claus-Jochen and Skopalik, Alexander and Stroh-Maraun, Nadja}},
booktitle = {{Proceedings of the 13th Workshop on Economics of Networks, Systems and Computation (NetEcon 2018)}},
isbn = {{978-1-4503-5916-0}},
location = {{Irvine, California, USA}},
pages = {{5:1--5:6}},
title = {{{Disaggregating User Evaluations Using the Shapley Value}}},
doi = {{10.1145/3230654.3230659}},
year = {{2018}},
}
@misc{3851,
author = {{Koop, Samuel}},
publisher = {{Universität Paderborn}},
title = {{{Congestion Games mit gewichteten Strategien}}},
year = {{2018}},
}
@inproceedings{17651,
abstract = {{Consider mitigating the effects of denial of service or of malicious traffic in networks by deleting edges. Edge deletion reduces the DoS or the number of the malicious flows, but it also inadvertently removes some of the desired flows. To model this important problem, we formulate two problems: (1) remove all the undesirable flows while minimizing the damage to the desirable ones and (2) balance removing the undesirable flows and not removing too many of the desirable flows. We prove these problems are equivalent to important theoretical problems, thereby being important not only practically but also theoretically, and very hard to approximate in a general network. We employ reductions to nonetheless approximate the problem and also provide a greedy approximation. When the network is a tree, the problems are still MAX SNP-hard, but we provide a greedy-based 2l-approximation algorithm, where l is the longest desirable flow. We also provide an algorithm, approximating the first and the second problem within {\$}{\$}2 {\backslash}sqrt{\{} 2{\backslash}left| E {\backslash}right| {\}}{\$}{\$}and {\$}{\$}2 {\backslash}sqrt{\{}2 ({\backslash}left| E {\backslash}right| + {\backslash}left| {\backslash}text {\{}undesirable flows{\}} {\backslash}right| ){\}}{\$}{\$}, respectively, where E is the set of the edges of the network. We also provide a fixed-parameter tractable (FPT) algorithm. Finally, if the tree has a root such that every flow in the tree flows on the path from the root to a leaf, we solve the problem exactly using dynamic programming.}},
author = {{Polevoy, Gleb and Trajanovski, Stojan and Grosso, Paola and de Laat, Cees}},
booktitle = {{Combinatorial Optimization and Applications}},
editor = {{Kim, Donghyun and Uma, R. N. and Zelikovsky, Alexander}},
isbn = {{978-3-030-04651-4}},
keywords = {{flow, Red-Blue Set Cover, Positive-Negative Partial Set Cover, approximation, tree, MAX SNP-hard, root, leaf, dynamic programming, FPT}},
pages = {{217--232}},
publisher = {{Springer International Publishing}},
title = {{{Removing Undesirable Flows by Edge Deletion}}},
year = {{2018}},
}
@article{17666,
abstract = {{Software Defined Networks (SDN) and Network Function Virtualisation (NFV) provide the basis for autonomous response and mitigation against attacks on networked computer infrastructures. We propose a new framework that uses SDNs and NFV to achieve this goal: Secure Autonomous Response Network (SARNET). In a SARNET, an agent running a control loop constantly assesses the security state of the network by means of observables. The agent reacts to and resolves security problems, while learning from its previous decisions. Two main metrics govern the decision process in a SARNET: impact and efficiency; these metrics can be used to compare and evaluate countermeasures and are the building blocks for self-learning SARNETs that exhibit autonomous response. In this paper we present the software implementation of the SARNET framework, evaluate it in a real-life network and discuss the tradeoffs between parameters used by the SARNET agent and the efficiency of its actions.}},
author = {{Koning, R. and de Graaff, B. and Polevoy, Gleb and Meijer, R. and de Laat, C. and Grosso, P.}},
issn = {{0167-739X}},
journal = {{Future Generation Computer Systems}},
keywords = {{Software defined networks, Network function virtualization, Cyber attacks, Cyber security, Defense efficiency, Overlay networks}},
title = {{{Measuring the efficiency of SDN mitigations against attacks on computer infrastructures}}},
doi = {{https://doi.org/10.1016/j.future.2018.08.011}},
year = {{2018}},
}
@article{669,
abstract = {{We study a new class of games which generalizes congestion games andits bottleneck variant. We introduce congestion games with mixed objectives to modelnetwork scenarios in which players seek to optimize for latency and bandwidths alike.We characterize the (non-)existence of pure Nash equilibria (PNE), the convergenceof improvement dynamics, the quality of equilibria and show the complexity of thedecision problem. For games that do not possess PNE we give bounds on the approx-imation ratio of approximate pure Nash equilibria.}},
author = {{Feldotto, Matthias and Leder, Lennart and Skopalik, Alexander}},
issn = {{1382-6905}},
journal = {{Journal of Combinatorial Optimization}},
number = {{4}},
pages = {{1145--1167}},
publisher = {{Springer Nature}},
title = {{{Congestion games with mixed objectives}}},
doi = {{10.1007/s10878-017-0189-y}},
volume = {{36}},
year = {{2018}},
}
@misc{1186,
author = {{Kemper, Arne}},
publisher = {{Universität Paderborn}},
title = {{{Pure Nash Equilibria in Robust Congestion Games via Potential Functions}}},
year = {{2018}},
}
@misc{1187,
author = {{Nachtigall, Marcel}},
publisher = {{Universität Paderborn}},
title = {{{Scenario-driven Strategy Analysis in a n-player Composition Game Model}}},
year = {{2018}},
}
@misc{1188,
author = {{Kempf, Jérôme}},
publisher = {{Universität Paderborn}},
title = {{{Learning deterministic bandit behaviour form compositions}}},
year = {{2018}},
}
@article{1369,
abstract = {{In budget games, players compete over resources with finite budgets. For every resource, a player has a specific demand and as a strategy, he chooses a subset of resources. If the total demand on a resource does not exceed its budget, the utility of each player who chose that resource equals his demand. Otherwise, the budget is shared proportionally. In the general case, pure Nash equilibria (NE) do not exist for such games. In this paper, we consider the natural classes of singleton and matroid budget games with additional constraints and show that for each, pure NE can be guaranteed. In addition, we introduce a lexicographical potential function to prove that every matroid budget game has an approximate pure NE which depends on the largest ratio between the different demands of each individual player.}},
author = {{Drees, Maximilian and Feldotto, Matthias and Riechers, Sören and Skopalik, Alexander}},
issn = {{1382-6905}},
journal = {{Journal of Combinatorial Optimization}},
publisher = {{Springer Nature}},
title = {{{Pure Nash equilibria in restricted budget games}}},
doi = {{10.1007/s10878-018-0269-7}},
year = {{2018}},
}
@inproceedings{112,
abstract = {{We study a model of selfish resource allocation that seeks to incorporate dependencies among resources as they exist in in modern networked environments. Our model is inspired by utility functions with constant elasticity of substitution (CES) which is a well-studied model in economics. We consider congestion games with different aggregation functions. In particular, we study $L_p$ norms and analyze the existence and complexity of (approximate) pure Nash equilibria. Additionally, we give an almost tight characterization based on monotonicity properties to describe the set of aggregation functions that guarantee the existence of pure Nash equilibria.}},
author = {{Feldotto, Matthias and Leder, Lennart and Skopalik, Alexander}},
booktitle = {{Proceedings of the 10th International Conference on Algorithms and Complexity (CIAC)}},
pages = {{222----233}},
title = {{{Congestion Games with Complementarities}}},
doi = {{10.1007/978-3-319-57586-5_19}},
year = {{2017}},
}
@inproceedings{113,
abstract = {{We study the computation of approximate pure Nash equilibria in Shapley value (SV) weighted congestion games, introduced in [19]. This class of games considers weighted congestion games in which Shapley values are used as an alternative (to proportional shares) for distributing the total cost of each resource among its users. We focus on the interesting subclass of such games with polynomial resource cost functions and present an algorithm that computes approximate pure Nash equilibria with a polynomial number of strategy updates. Since computing a single strategy update is hard, we apply sampling techniques which allow us to achieve polynomial running time. The algorithm builds on the algorithmic ideas of [7], however, to the best of our knowledge, this is the first algorithmic result on computation of approximate equilibria using other than proportional shares as player costs in this setting. We present a novel relation that approximates the Shapley value of a player by her proportional share and vice versa. As side results, we upper bound the approximate price of anarchy of such games and significantly improve the best known factor for computing approximate pure Nash equilibria in weighted congestion games of [7].}},
author = {{Feldotto, Matthias and Gairing, Martin and Kotsialou, Grammateia and Skopalik, Alexander}},
booktitle = {{Proceedings of the 13th International Conference on Web and Internet Economics (WINE)}},
title = {{{Computing Approximate Pure Nash Equilibria in Shapley Value Weighted Congestion Games}}},
doi = {{10.1007/978-3-319-71924-5_14}},
year = {{2017}},
}
@inproceedings{17652,
author = {{Polevoy, Gleb and Trajanovski, Stojan and Grosso, Paola and de Laat, Cees}},
booktitle = {{Combinatorial Optimization and Applications: 11th International Conference, COCOA 2017, Shanghai, China, December 16-18, 2017, Proceedings, Part I}},
isbn = {{978-3-319-71150-8}},
keywords = {{flow, filter, MMSA, set cover, approximation, local ratio algorithm}},
pages = {{3--17}},
publisher = {{Springer International Publishing}},
title = {{{Filtering Undesirable Flows in Networks}}},
doi = {{10.1007/978-3-319-71150-8_1}},
year = {{2017}},
}
@inproceedings{17653,
author = {{Polevoy, Gleb and de Weerdt, M.M.}},
booktitle = {{Proceedings of the 29th Benelux Conference on Artificial Intelligence}},
keywords = {{interaction, reciprocation, contribute, shared effort, curbing, convergence, threshold, Nash equilibrium, social welfare, efficiency, price of anarchy, price of stability}},
publisher = {{Springer}},
title = {{{Reciprocation Effort Games}}},
year = {{2017}},
}
@inproceedings{17654,
author = {{Polevoy, Gleb and de Weerdt, M.M.}},
booktitle = {{Proceedings of the 29th Benelux Conference on Artificial Intelligence}},
keywords = {{agents, projects, contribute, shared effort game, competition, quota, threshold, Nash equilibrium, social welfare, efficiency, price of anarchy, price of stability}},
publisher = {{Springer}},
title = {{{Competition between Cooperative Projects}}},
year = {{2017}},
}
@inproceedings{59,
abstract = {{We consider a scheduling problem on $m$ identical processors sharing an arbitrarily divisible resource. In addition to assigning jobs to processors, the scheduler must distribute the resource among the processors (e.g., for three processors in shares of 20\%, 15\%, and 65\%) and adjust this distribution over time. Each job $j$ comes with a size $p_j \in \mathbb{R}$ and a resource requirement $r_j > 0$. Jobs do not benefit when receiving a share larger than $r_j$ of the resource. But providing them with a fraction of the resource requirement causes a linear decrease in the processing efficiency. We seek a (non-preemptive) job and resource assignment minimizing the makespan.Our main result is an efficient approximation algorithm which achieves an approximation ratio of $2 + 1/(m-2)$. It can be improved to an (asymptotic) ratio of $1 + 1/(m-1)$ if all jobs have unit size. Our algorithms also imply new results for a well-known bin packing problem with splittable items and a restricted number of allowed item parts per bin.Based upon the above solution, we also derive an approximation algorithm with similar guarantees for a setting in which we introduce so-called tasks each containing several jobs and where we are interested in the average completion time of tasks (a task is completed when all its jobs are completed).}},
author = {{Kling, Peter and Mäcker, Alexander and Riechers, Sören and Skopalik, Alexander}},
booktitle = {{Proceedings of the 29th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA)}},
pages = {{123----132}},
title = {{{Sharing is Caring: Multiprocessor Scheduling with a Sharable Resource}}},
doi = {{10.1145/3087556.3087578}},
year = {{2017}},
}
@inproceedings{66,
abstract = {{In budget games, players compete over resources with finite budgets. For every resource, a player has a specific demand and as a strategy, he chooses a subset of resources. If the total demand on a resource does not exceed its budget, the utility of each player who chose that resource equals his demand. Otherwise, the budget is shared proportionally. In the general case, pure Nash equilibria (NE) do not exist for such games. In this paper, we consider the natural classes of singleton and matroid budget games with additional constraints and show that for each, pure NE can be guaranteed. In addition, we introduce a lexicographical potential function to prove that every matroid budget game has an approximate pure NE which depends on the largest ratio between the different demands of each individual player.}},
author = {{Drees, Maximilian and Feldotto, Matthias and Riechers, Sören and Skopalik, Alexander}},
booktitle = {{Proceedings of the 23rd International Computing and Combinatorics Conference (COCOON)}},
pages = {{175----187}},
title = {{{Pure Nash Equilibria in Restricted Budget Games}}},
doi = {{10.1007/978-3-319-62389-4_15}},
year = {{2017}},
}
@misc{1073,
author = {{Nachtigall, Simon}},
publisher = {{Universität Paderborn}},
title = {{{Sortieren dynamischer Daten}}},
year = {{2017}},
}
@misc{1074,
author = {{Pukrop, Simon}},
publisher = {{Universität Paderborn}},
title = {{{Robuste Optimierung in Congestion Games}}},
year = {{2017}},
}
@misc{1080,
author = {{Bürmann, Jan}},
publisher = {{Universität Paderborn}},
title = {{{Complexity of Signalling in Routing Games under Uncertainty}}},
year = {{2017}},
}
@misc{1081,
author = {{Vijayalakshmi, Vipin Ravindran}},
publisher = {{Universität Paderborn}},
title = {{{Bounding the Inefficiency of Equilibria in Congestion Games under Taxation}}},
year = {{2017}},
}
@inproceedings{1094,
abstract = {{Many university students struggle with motivational problems, and gamification has the potential to address these problems. However, gamification is hardly used in education, because current approaches to gamification require instructors to engage in the time-consuming preparation of their course contents for use in quizzes, mini-games and the like. Drawing on research on limited attention and present bias, we propose a "lean" approach to gamification, which relies on gamifying learning activities (rather than learning contents) and increasing their salience. In this paper, we present the app StudyNow that implements such a lean gamification approach. With this app, we aim to enable more students and instructors to benefit from the advantages of gamification.}},
author = {{Feldotto, Matthias and John, Thomas and Kundisch, Dennis and Hemsen, Paul and Klingsieck, Katrin and Skopalik, Alexander}},
booktitle = {{Proceedings of the 12th International Conference on Design Science Research in Information Systems and Technology (DESRIST)}},
pages = {{462--467}},
title = {{{Making Gamification Easy for the Professor: Decoupling Game and Content with the StudyNow Mobile App}}},
doi = {{10.1007/978-3-319-59144-5_32}},
year = {{2017}},
}
@inproceedings{1095,
abstract = {{Many university students struggle with motivational problems, and gamification has the potential to address these problems. However, using gamification currently is rather tedious and time-consuming for instructors because current approaches to gamification require instructors to engage in the time-consuming preparation of course contents (e.g., for quizzes or mini-games). In reply to this issue, we propose a “lean” approach to gamification, which relies on gamifying learning activities rather than learning contents. The learning activities that are gamified in the lean approach can typically be drawn from existing course syllabi (e.g., attend certain lectures, hand in assignments, read book chapters and articles). Hence, compared to existing approaches, lean gamification substantially lowers the time requirements posed on instructors for gamifying a given course. Drawing on research on limited attention and the present bias, we provide the theoretical foundation for the lean gamification approach. In addition, we present a mobile application that implements lean gamification and outline a mixed-methods study that is currently under way for evaluating whether lean gamification does indeed have the potential to increase students’ motivation. We thereby hope to allow more students and instructors to benefit from the advantages of gamification. }},
author = {{John, Thomas and Feldotto, Matthias and Hemsen, Paul and Klingsieck, Katrin and Kundisch, Dennis and Langendorf, Mike}},
booktitle = {{Proceedings of the 25th European Conference on Information Systems (ECIS)}},
pages = {{2970--2979}},
title = {{{Towards a Lean Approach for Gamifying Education}}},
year = {{2017}},
}
@phdthesis{200,
author = {{Drees, Maximilian}},
publisher = {{Universität Paderborn}},
title = {{{Existence and Properties of Pure Nash Equilibria in Budget Games}}},
year = {{2016}},
}
@misc{210,
author = {{Leder, Lennart}},
publisher = {{Universität Paderborn}},
title = {{{Congestion Games with Mixed Objectives}}},
year = {{2016}},
}
@inproceedings{17655,
author = {{Polevoy, Gleb and de Weerdt, M.M. and Jonker, C.M.}},
booktitle = {{Proceedings of the 2016 European Conference on Artificial Intelligence}},
keywords = {{agents, action, repeated reciprocation, fixed, floating, network, Nash equilibrium, social welfare, price of anarchy, price of stability, convex combination}},
pages = {{417--425}},
title = {{{The Game of Reciprocation Habits}}},
doi = {{10.3233/978-1-61499-672-9-417}},
volume = {{Volume 285: ECAI 2016}},
year = {{2016}},
}
@inproceedings{17656,
author = {{Polevoy, Gleb and de Weerdt, Mathijs and Jonker, Catholijn}},
booktitle = {{Proceedings of the 2016 International Conference on Autonomous Agents and Multiagent Systems}},
isbn = {{978-1-4503-4239-1}},
keywords = {{agent's influence, behavior, convergence, perron-frobenius, reciprocal interaction, repeated reciprocation}},
pages = {{1431--1432}},
publisher = {{International Foundation for Autonomous Agents and Multiagent Systems}},
title = {{{The Convergence of Reciprocation}}},
year = {{2016}},
}
@inproceedings{209,
abstract = {{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.}},
author = {{Feldotto, Matthias and Leder, Lennart and Skopalik, Alexander}},
booktitle = {{Proceedings of the 10th Annual International Conference on Combinatorial Optimization and Applications (COCOA)}},
pages = {{655----669}},
title = {{{Congestion Games with Mixed Objectives}}},
doi = {{10.1007/978-3-319-48749-6_47}},
year = {{2016}},
}
@misc{1082,
author = {{Handirk, Tobias}},
publisher = {{Universität Paderborn}},
title = {{{Über die Rolle von Informationen in Verkehrsnetzwerken}}},
year = {{2016}},
}
@article{159,
abstract = {{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.}},
author = {{Harks, Tobias and Höfer, Martin and Schewior, Kevin and Skopalik, Alexander}},
journal = {{IEEE/ACM Transactions on Networking}},
number = {{4}},
pages = {{2553 -- 2562}},
publisher = {{IEEE}},
title = {{{Routing Games With Progressive Filling}}},
doi = {{10.1109/TNET.2015.2468571}},
year = {{2016}},
}
@inproceedings{149,
abstract = {{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).}},
author = {{Drees, Maximilian and Feldkord, Björn and Skopalik, Alexander}},
booktitle = {{Proceedings of the 10th Annual International Conference on Combinatorial Optimization and Applications (COCOA)}},
pages = {{593----607}},
title = {{{Strategic Online Facility Location}}},
doi = {{10.1007/978-3-319-48749-6_43}},
year = {{2016}},
}
@article{145,
abstract = {{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. }},
author = {{Feldotto, Matthias and Graffi, Kalman}},
journal = {{Concurrency and Computation: Practice and Experience}},
number = {{5}},
pages = {{1655--1677}},
publisher = {{Wiley Online Library}},
title = {{{Systematic evaluation of peer-to-peer systems using PeerfactSim.KOM}}},
doi = {{10.1002/cpe.3716}},
volume = {{28}},
year = {{2016}},
}
@misc{251,
author = {{Pfannschmidt, Karlson}},
publisher = {{Universität Paderborn}},
title = {{{Solving the aggregated bandits problem}}},
year = {{2015}},
}
@article{320,
abstract = {{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.}},
author = {{Caragiannis, Ioannis and Fanelli, Angelo and Gravin, Nick and Skopalik, Alexander}},
journal = {{Transactions on Economics and Computation}},
number = {{1}},
publisher = {{ACM}},
title = {{{Approximate Pure Nash Equilibria in Weighted Congestion Games: Existence, Efficient Computation, and Structure}}},
doi = {{10.1145/2614687}},
volume = {{3}},
year = {{2015}},
}
@misc{316,
author = {{Pautz, Jannis}},
publisher = {{Universität Paderborn}},
title = {{{Budget Games with priced strategies}}},
year = {{2015}},
}
@inproceedings{271,
abstract = {{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.}},
author = {{Drees, Maximilian and Feldotto, Matthias and Riechers, Sören and Skopalik, Alexander}},
booktitle = {{Proceedings of the 8th International Symposium on Algorithmic Game Theory (SAGT)}},
pages = {{178--189}},
title = {{{On Existence and Properties of Approximate Pure Nash Equilibria in Bandwidth Allocation Games}}},
doi = {{10.1007/978-3-662-48433-3_14}},
year = {{2015}},
}
@misc{277,
author = {{Kothe, Nils}},
publisher = {{Universität Paderborn}},
title = {{{Multilevel Netzwerk Spiele mit konstanten Entfernungen im Highspeed-Netzwerk}}},
year = {{2015}},
}
@article{17657,
abstract = {{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.}},
author = {{Cohen, R. and Polevoy, Gleb}},
issn = {{2168-7161}},
journal = {{Cloud Computing, IEEE Transactions on}},
keywords = {{Approximation algorithms, Approximation methods, Bandwidth, Cloud computing, Routing, Schedules, Scheduling}},
number = {{99}},
pages = {{1--1}},
title = {{{Inter-Datacenter Scheduling of Large Data Flows}}},
doi = {{10.1109/TCC.2015.2487964}},
volume = {{PP}},
year = {{2015}},
}
@article{17658,
abstract = {{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. }},
author = {{Bar-Yehuda, Reuven and Polevoy, Gleb and Rawitz, Dror}},
issn = {{0166-218X}},
journal = {{Discrete Applied Mathematics }},
keywords = {{Local ratio}},
pages = {{23 -- 36}},
publisher = {{Elsevier}},
title = {{{Bandwidth allocation in cellular networks with multiple interferences}}},
doi = {{http://dx.doi.org/10.1016/j.dam.2015.05.013}},
volume = {{194}},
year = {{2015}},
}
@inproceedings{370,
abstract = {{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. }},
author = {{Harks, Tobias and Höfer, Martin and Schewior, Kevin and Skopalik, Alexander}},
booktitle = {{Proceedings of the 33rd Annual IEEE International Conference on Computer Communications (INFOCOM'14)}},
pages = {{352--360}},
title = {{{Routing Games with Progressive Filling}}},
doi = {{10.1109/TNET.2015.2468571}},
year = {{2014}},
}
@misc{373,
author = {{Pahl, David}},
publisher = {{Universität Paderborn}},
title = {{{Reputationssysteme für zusammengesetzte Dienstleistungen}}},
year = {{2014}},
}
@inproceedings{17659,
author = {{Polevoy, Gleb and Trajanovski, Stojan and de Weerdt, Mathijs M.}},
booktitle = {{Proceedings of the 2014 International Conference on Autonomous Agents and Multi-agent Systems}},
isbn = {{978-1-4503-2738-1}},
keywords = {{competition, equilibrium, market, models, shared effort games, simulation}},
pages = {{861--868}},
publisher = {{International Foundation for Autonomous Agents and Multiagent Systems}},
title = {{{Nash Equilibria in Shared Effort Games}}},
year = {{2014}},
}
@inproceedings{17660,
author = {{Polevoy, Gleb and de Weerdt, Mathijs M.}},
booktitle = {{Proceedings of the 2014 International Conference on Autonomous Agents and Multi-agent Systems}},
isbn = {{978-1-4503-2738-1}},
keywords = {{dynamics, emotion modeling, negotiation, network interaction, shared effort game}},
pages = {{1741--1742}},
publisher = {{International Foundation for Autonomous Agents and Multiagent Systems}},
title = {{{Improving Human Interaction in Crowdsensing}}},
year = {{2014}},
}
@inproceedings{17661,
author = {{King, Thomas C. and Liu, Qingzhi and Polevoy, Gleb and de Weerdt, Mathijs and Dignum, Virginia and van Riemsdijk, M. Birna and Warnier, Martijn}},
booktitle = {{Proceedings of the 2014 International Conference on Autonomous Agents and Multi-agent Systems}},
isbn = {{978-1-4503-2738-1}},
keywords = {{crowd-sensing, crowdsourcing, data aggregation, game theory, norms, reciprocation, self interested agents, simulation}},
pages = {{1651--1652}},
publisher = {{International Foundation for Autonomous Agents and Multiagent Systems}},
title = {{{Request Driven Social Sensing}}},
year = {{2014}},
}
@article{17662,
author = {{Polevoy, Gleb and Smorodinsky, Rann and Tennenholtz, Moshe}},
issn = {{2167-8375}},
journal = {{ACM Trans. Econ. Comput.}},
keywords = {{Competition, efficiency, equilibrium, market, social welfare}},
number = {{1}},
pages = {{1:1--1:16}},
publisher = {{ACM}},
title = {{{Signaling Competition and Social Welfare}}},
doi = {{10.1145/2560766}},
volume = {{2}},
year = {{2014}},
}
@inproceedings{451,
abstract = {{We introduce the concept of budget games. Players choose a set of tasks and each task has a certain demand on every resource in the game. Each resource has a budget. If the budget is not enough to satisfy the sum of all demands, it has to be shared between the tasks. We study strategic budget games, where the budget is shared proportionally. We also consider a variant in which the order of the strategic decisions influences the distribution of the budgets. The complexity of the optimal solution as well as existence, complexity and quality of equilibria are analysed. Finally, we show that the time an ordered budget game needs to convergence towards an equilibrium may be exponential.}},
author = {{Drees, Maximilian and Riechers, Sören and Skopalik, Alexander}},
booktitle = {{Proceedings of the 7th International Symposium on Algorithmic Game Theory (SAGT)}},
editor = {{Lavi, Ron}},
pages = {{110--121}},
title = {{{Budget-restricted utility games with ordered strategic decisions}}},
doi = {{10.1007/978-3-662-44803-8_10}},
year = {{2014}},
}