TY - CONF AB - Consider the practical goal of making a desired action profile played, when the planner can only change the payoffs, bound by stringent constraints. Applications include motivating people to choose the closest school, the closest subway station, or to coordinate on a communication protocol or an investment strategy. Employing subsidies and tolls, we adjust the game so that choosing this predefined action profile becomes strictly dominant. Inspired mainly by the work of Monderer and Tennenholtz, where the promised subsidies do not materialise in the not played profiles, we provide a fair and individually rational game adjustment, such that the total outside investments sum up to zero at any profile, thereby facilitating easy and frequent usage of our adjustment without bearing costs, even if some players behave unexpectedly. The resultant action profile itself needs no adjustment. Importantly, we also prove that our adjustment minimises the general transfer among all such adjustments, counting the total subsidising and taxation. AU - Polevoy, Gleb AU - Dziubiński, Marcin ED - De Raedt, Luc ID - 34040 KW - adjustment KW - strictly dominant KW - fairness KW - individually rational KW - transfer KW - tax KW - subsidy T2 - Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence TI - Fair, Individually Rational and Cheap Adjustment ER - TY - CONF AB - 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. AU - Koning, Ralph AU - Polevoy, Gleb AU - Meijer, Lydia AU - de Laat, Cees AU - Grosso, Paola ID - 17667 KW - computer network security KW - multinetwork environments KW - multidomain defensive action KW - task execution order KW - timing influence defense efficiency KW - distributed attacks KW - collaborative security defence approach KW - minimize propagation approach KW - minimize countermeasure approach KW - counteract everywhere approach KW - Conferences KW - Cloud computing KW - Computer crime KW - Edge computing KW - Security KW - Defense Approaches KW - Multi-Domain Defense KW - Collaborative Defense KW - Defense Algorithms KW - Computer Networks SN - null T2 - 2019 6th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/ 2019 5th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom) TI - Approaches for Collaborative Security Defences in Multi Network Environments ER - TY - THES AB - 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. AU - Feldotto, Matthias ID - 8080 TI - Approximate Pure Nash Equilibria in Congestion, Opinion Formation and Facility Location Games ER - TY - CONF AB - 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. AU - Lazos, Philip AU - Goldberg, Paul AU - Skopalik, Alexander AU - Gerstgrasser, Matthias AU - de Keijzer, Bart ID - 5471 T2 - Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI) TI - Multi-unit Bilateral Trade ER - TY - CONF AB - 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. AU - Feldotto, Matthias AU - Lenzner, Pascal AU - Molitor, Louise AU - Skopalik, Alexander ID - 10281 T2 - Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems TI - From Hotelling to Load Balancing: Approximation and the Principle of Minimum Differentiation ER - TY - CONF AB - 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. AU - Feldkord, Björn AU - Feldotto, Matthias AU - Gupta, Anupam AU - Guruganesh, Guru AU - Kumar, Amit AU - Riechers, Sören AU - Wajc, David ED - Chatzigiannakis, Ioannis ED - Kaklamanis, Christos ED - Marx, Dániel ED - Sannella, Donald ID - 2484 SN - 1868-8969 T2 - 45th International Colloquium on Automata, Languages, and Programming (ICALP 2018) TI - Fully-Dynamic Bin Packing with Little Repacking VL - 107 ER - TY - CONF AB - 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. AU - Feldotto, Matthias AU - Haake, Claus-Jochen AU - Skopalik, Alexander AU - Stroh-Maraun, Nadja ID - 2831 SN - 978-1-4503-5916-0 T2 - Proceedings of the 13th Workshop on Economics of Networks, Systems and Computation (NetEcon 2018) TI - Disaggregating User Evaluations Using the Shapley Value ER - TY - GEN AU - Koop, Samuel ID - 3851 TI - Congestion Games mit gewichteten Strategien ER - TY - CONF AB - 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. AU - Polevoy, Gleb AU - Trajanovski, Stojan AU - Grosso, Paola AU - de Laat, Cees ED - Kim, Donghyun ED - Uma, R. N. ED - Zelikovsky, Alexander ID - 17651 KW - flow KW - Red-Blue Set Cover KW - Positive-Negative Partial Set Cover KW - approximation KW - tree KW - MAX SNP-hard KW - root KW - leaf KW - dynamic programming KW - FPT SN - 978-3-030-04651-4 T2 - Combinatorial Optimization and Applications TI - Removing Undesirable Flows by Edge Deletion ER - TY - JOUR AB - 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. AU - Koning, R. AU - de Graaff, B. AU - Polevoy, Gleb AU - Meijer, R. AU - de Laat, C. AU - Grosso, P. ID - 17666 JF - Future Generation Computer Systems KW - Software defined networks KW - Network function virtualization KW - Cyber attacks KW - Cyber security KW - Defense efficiency KW - Overlay networks SN - 0167-739X TI - Measuring the efficiency of SDN mitigations against attacks on computer infrastructures ER - TY - JOUR AB - 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. AU - Feldotto, Matthias AU - Leder, Lennart AU - Skopalik, Alexander ID - 669 IS - 4 JF - Journal of Combinatorial Optimization SN - 1382-6905 TI - Congestion games with mixed objectives VL - 36 ER - TY - GEN AU - Kemper, Arne ID - 1186 TI - Pure Nash Equilibria in Robust Congestion Games via Potential Functions ER - TY - GEN AU - Nachtigall, Marcel ID - 1187 TI - Scenario-driven Strategy Analysis in a n-player Composition Game Model ER - TY - GEN AU - Kempf, Jérôme ID - 1188 TI - Learning deterministic bandit behaviour form compositions ER - TY - JOUR AB - 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. AU - Drees, Maximilian AU - Feldotto, Matthias AU - Riechers, Sören AU - Skopalik, Alexander ID - 1369 JF - Journal of Combinatorial Optimization SN - 1382-6905 TI - Pure Nash equilibria in restricted budget games ER - TY - CONF AB - 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. AU - Feldotto, Matthias AU - Leder, Lennart AU - Skopalik, Alexander ID - 112 T2 - Proceedings of the 10th International Conference on Algorithms and Complexity (CIAC) TI - Congestion Games with Complementarities ER - TY - CONF AB - 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]. AU - Feldotto, Matthias AU - Gairing, Martin AU - Kotsialou, Grammateia AU - Skopalik, Alexander ID - 113 T2 - Proceedings of the 13th International Conference on Web and Internet Economics (WINE) TI - Computing Approximate Pure Nash Equilibria in Shapley Value Weighted Congestion Games ER - TY - CONF AU - Polevoy, Gleb AU - Trajanovski, Stojan AU - Grosso, Paola AU - de Laat, Cees ID - 17652 KW - flow KW - filter KW - MMSA KW - set cover KW - approximation KW - local ratio algorithm SN - 978-3-319-71150-8 T2 - Combinatorial Optimization and Applications: 11th International Conference, COCOA 2017, Shanghai, China, December 16-18, 2017, Proceedings, Part I TI - Filtering Undesirable Flows in Networks ER - TY - CONF AU - Polevoy, Gleb AU - de Weerdt, M.M. ID - 17653 KW - interaction KW - reciprocation KW - contribute KW - shared effort KW - curbing KW - convergence KW - threshold KW - Nash equilibrium KW - social welfare KW - efficiency KW - price of anarchy KW - price of stability T2 - Proceedings of the 29th Benelux Conference on Artificial Intelligence TI - Reciprocation Effort Games ER - TY - CONF AU - Polevoy, Gleb AU - de Weerdt, M.M. ID - 17654 KW - agents KW - projects KW - contribute KW - shared effort game KW - competition KW - quota KW - threshold KW - Nash equilibrium KW - social welfare KW - efficiency KW - price of anarchy KW - price of stability T2 - Proceedings of the 29th Benelux Conference on Artificial Intelligence TI - Competition between Cooperative Projects ER -