Redundancy Analysis of the Railway Network of Hungary

Available alternative routes on which traffic can be rerouted in the case of disruptions are vital for transportation networks. Line sections with less traffic under normal operational conditions but with increased importance in the case of disruptions are identified in the railway network of Hungary by using a weighted directed graph. To describe the goodness of the individual alternative routes the so-called redundancy index is used. The results show that the structure of the network is good, but the lines with the highest redundancy (lines No. 80, 2, 4 and 77 according to the numbering of the national railway operator, M\'AV) are mostly single tracked and in many cases the line speed is low. The building of additional tracks and electrifying these lines while still maintaining the existing diesel locomotives for the case of disruptions of the electric support are the keys to make the performance of the rather dense railway network of Hungary sustainable.Comment: 8 pages, 4 figures. arXiv admin note: text overlap with arXiv:2005.1280

Interdependent Defense Games with Applications to Internet Security at the Level of Autonomous Systems

We propose interdependent defense (IDD) games, a computational game-theoretic framework to study aspects of the interdependence of risk and security in multi-agent systems under deliberate external attacks. Our model builds upon interdependent security (IDS) games, a model by Heal and Kunreuther that considers the source of the risk to be the result of a fixed randomized-strategy. We adapt IDS games to model the attacker’s deliberate behavior. We define the attacker’s pure-strategy space and utility function and derive appropriate cost functions for the defenders. We provide a complete characterization of mixed-strategy Nash equilibria (MSNE), and design a simple polynomial-time algorithm for computing all of them for an important subclass of IDD games. We also show that an efficient algorithm to determine whether some attacker’s strategy can be a part of an MSNE in an instance of IDD games is unlikely to exist. Yet, we provide a dynamic programming (DP) algorithm to compute an approximate MSNE when the graph/network structure of the game is a directed tree with a single source. We also show that the DP algorithm is a fully polynomial-time approximation scheme. In addition, we propose a generator of random instances of IDD games based on the real-world Internet-derived graph at the level of autonomous systems (≈27 K nodes and ≈100 K edges as measured in March 2010 by the DIMES project). We call such games Internet games. We introduce and empirically evaluate two heuristics from the literature on learning-in-games, best-response gradient dynamics (BRGD) and smooth best-response dynamics (SBRD), to compute an approximate MSNE in IDD games with arbitrary graph structures, such as randomly-generated instances of Internet games. In general, preliminary experiments applying our proposed heuristics are promising. Our experiments show that, while BRGD is a useful technique for the case of Internet games up to certain approximation level, SBRD is more efficient and provides better approximations than BRGD. Finally, we discuss several extensions, future work, and open problems

Deception in Game Theory: A Survey and Multiobjective Model

Game theory is the study of mathematical models of conflict. It provides tools for analyzing dynamic interactions between multiple agents and (in some cases) across multiple interactions. This thesis contains two scholarly articles. The first article is a survey of game-theoretic models of deception. The survey describes the ways researchers use game theory to measure the practicality of deception, model the mechanisms for performing deception, analyze the outcomes of deception, and respond to, or mitigate the effects of deception. The survey highlights several gaps in the literature. One important gap concerns the benefit-cost-risk trade-off made during deception planning. To address this research gap, the second article introduces a novel approach for modeling these trade-offs. The approach uses a game theoretic model of deception to define a new multiobjective optimization problem called the deception design problem (DDP). Solutions to the DDP provide courses of deceptive action that are efficient in terms of their benefit, cost, and risk to the deceiver. A case study based on the output of an air-to-air combat simulator demonstrates the DDP in a 7 x 7 normal form game. This approach is the first to evaluate benefit, cost, and risk in a single game theoretic model of deception