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Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems

作者： Hau Chan Mohammad T. Irfan Cuong Viet Than University of Nebraska-Lincoln Lincoln NE USA Bowdoin College Brunswick ME USA

ISBN: (纸本)9781450375184

We propose a game-theoretic approach to generalizing the classical Schelling model. At the core of our model are two features that did not receive much attention before. First, we allow multiple individuals to occupy the same location. Second, each individual's choice of location is influenced by their social network neighbors that also choose the same location. In addition, an individual's choice is influenced by others in the adjacent locations in a network-structured way, which captures the main spirit of the classical Schelling model and its numerous extensions. Our solution concept is a stable configuration represented as a pure-strategy Nash equilibrium (PSNE). We show that even for various special cases of the problem, computing or counting PSNE is provably hard. We give algorithms for computing PSNE, including efficient algorithms for several special cases. We highlight some of the attractive features of our model, such as predicting very few PSNE, through experiments.

关键词： propagation algorithms schelling model social influence nash equilibrium social networks computational game theory

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A Potential Reduction Algorithm for Two-Person Zero-Sum Mean Payoff Stochastic games

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DYNAMIC gameS AND APPLICATIONS 2018年第1期8卷 22-41页

作者： Boros, Endre Elbassioni, Khaled Gurvich, Vladimir Makino, Kazuhisa Rutgers State Univ MSIS Dept RBS & RUTCOR 100 Rockafeller Rd Piscataway NJ 08854 USA Masdar Inst Sci & Technol BO Box 54224 Abu Dhabi U Arab Emirates Higher Sch Econ Res Inst Moscow Russia Kyoto Univ Res Inst Math Sci RIMS Kyoto 6068502 Japan

We suggest a new algorithm for two-person zero-sum undiscounted stochastic games focusing on stationary strategies. Given a positive real , let us call a stochastic game -ergodic, if its values from any two initial positions differ by at most . The proposed new algorithm outputs for every in finite time either a pair of stationary strategies for the two players guaranteeing that the values from any initial positions are within an -range, or identifies two initial positions u and v and corresponding stationary strategies for the players proving that the game values starting from u and v are at least apart. In particular, the above result shows that if a stochastic game is -ergodic, then there are stationary strategies for the players proving -ergodicity. This result strengthens and provides a constructive version of an existential result by Vrieze (Stochastic games with finite state and action spaces. PhD thesis, Centrum voor Wiskunde en Informatica, Amsterdam, 1980) claiming that if a stochastic game is 0-ergodic, then there are -optimal stationary strategies for every . The suggested algorithm is based on a potential transformation technique that changes the range of local values at all positions without changing the normal form of the game.

关键词： Undiscounted stochastic games Limiting average payoff Mean payoff Local reward Potential transformation computational game theory

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The Power of Context in Networks: Ideal Point Models with Social Interactions 17

The Power of Context in Networks: Ideal Point Models with So...

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17th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS)

作者： Irfan, Mohammad T. Gordon, Tucker Bowdoin Coll Brunswick ME 04011 USA Booz Allen Hamilton Inc Mclean VA 22102 USA

ISBN: (纸本)9781450356497

game theory has been widely used for modeling strategic behaviors in networked multiagent systems. However, the context within which these strategic behaviors take place has received limited attention. We present a model of strategic behavior in networks that incorporates the behavioral context. We focus on the contextual aspects of congressional voting. A senator's decision to vote yea or nay on a bill comes as a result of their ideologies, agendas, and their interactions with other senators. One salient model in political science is the ideal point model, which assigns each senator and each bill a number on the real line of political spectrum. These points then allow for prediction of future voting behavior. We extend the classical ideal point model with network-structured interactions among senators. In contrast to the ideal point model's prediction of individual voting behavior, we predict joint voting behaviors in a game-theoretic fashion. Our model also includes the characteristics of a bill. This allows it to outperform previous models that solely focus on the networked interactions among senators with no bill-specific parameters. We focus on two fundamental questions: learning the model using real-world data and computing stable outcomes of the model in order to predict joint voting behaviors. We demonstrate the effectiveness of our model through experiments using data from the 114th U.S. Congress.

关键词： computational game theory social networks machine learning congressional voting influence in networks

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Non-Zero-Sum Nonlinear Network Path Interdiction with an Application to Inspection in Terror Networks

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NAVAL RESEARCH LOGISTICS 2017年第2期64卷 139-153页

作者： Goldberg, Noam Bar Ilan Univ Dept Management Ramat Gan Israel

A simultaneous non-zero-sum game is modeled to extend the classical network interdiction problem. In this model, an interdictor (e.g., an enforcement agent) decides how much of an inspection resource to spend along each arc in the network to capture a smuggler. The smuggler (randomly) selects a commodity to smugglea source and destination pair of nodes, and also a corresponding path for traveling between the given pair of nodes. This model is motivated by a terrorist organization that can mobilize its human, financial, or weapon resources to carry out an attack at one of several potential target destinations. The probability of evading each of the network arcs nonlinearly decreases in the amount of resource that the interdictor spends on its inspection. We show that under reasonable assumptions with respect to the evasion probability functions, (approximate) Nash equilibria of this game can be determined in polynomial time;depending on whether the evasion functions are exponential or general logarithmically-convex functions, exact Nash equilibria or approximate Nash equilibria, respectively, are computed. (c) 2017 Wiley Periodicals, Inc.

关键词： network interdiction non-zero-sum game computational game theory Nash equilibrium inspection game Ellipsoid method convex optimization resource allocation

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Scarce-resource capacity sharing in cognitive radio environments: a new game theoretical model

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TELECOMMUNICATION SYSTEMS 2017年第2期66卷 331-342页

作者： Cremene, Ligia Gasko, Noemi Cremene, Marcel Suciu, Mihai Vlaicu, Aurel Dumitrescu, D. Tech Univ Cluj Napoca Commun Dept Cluj Napoca Romania Babes Bolyai Univ Cluj Napoca Comp Sci Dept Cluj Napoca Romania

The paper proposes a general game theoretical model, called capacity demand game, for treating simultaneous capacity requests in scarce-resource cognitive radio (CR) environments. The approach is that of non-cooperative games describing CR interactions in terms of radio resource access. Experiments reveal stable states (equilibria) that favour an equitable usage of radio resources to the benefit of all participants. Several equilibria are detected and discussed: Nash (NE), Pareto, joint Nash-Pareto, and Lorenz equilibrium.

关键词： Emerging communications systems Cognitive radio computational game theory Small cells Resource access Capacity sharing

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The Power of Context in Networks: Ideal Point Models with Social Interactions 18

The Power of Context in Networks: Ideal Point Models with So...

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Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems

作者： Mohammad T. Irfan Tucker Gordon Bowdoin College Brunswick ME USA Booz Allen Hamilton Inc. McLean VA USA

game theory has been widely used for modeling strategic behaviors in networked multiagent systems. However, the context within which these strategic behaviors take place has received limited attention. We present a model of strategic behavior in networks that incorporates the behavioral context. We focus on the contextual aspects of congressional voting. A senator's decision to vote yea or nay on a bill comes as a result of their ideologies, agendas, and their interactions with other senators. One salient model in political science is the ideal point model , which assigns each senator and each bill a number on the real line of political spectrum. These points then allow for prediction of future voting behavior. We extend the classical ideal point model with network-structured interactions among senators. In contrast to the ideal point model's prediction of individual voting behavior, we predict joint voting behaviors in a game-theoretic fashion. Our model also includes the characteristics of a bill. This allows it to outperform previous models that solely focus on the networked interactions among senators with no bill-specific parameters. We focus on two fundamental questions: learning the model using real-world data and computing stable outcomes of the model in order to predict joint voting behaviors. We demonstrate the effectiveness of our model through experiments using data from the 114th U.S. Congress.

关键词： influence in networks machine learning computational game theory social networks congressional voting

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Synthesis of Joint Control and Active Sensing Strategies Under Temporal Logic Constraints

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2016年第11期61卷 3464-3476页

作者： Fu, Jie Topcu, Ufuk Worcester Polytech Inst Dept Elect & Comp Engn Worcester MA 01604 USA Univ Texas Austin Dept Aerosp Engn & Engn Mech Austin TX 78712 USA

This paper proposes an approach to control of discrete systems with incomplete information and sensing capabilities, with respect to temporal logic constraints. The approach introduces active sensing to alleviate computational effort in control design for systems interacting with uncontrollable environments under incomplete information. Particularly, it transforms a deterministic controller under complete information into a randomized, observation-based controller. Interleaving the latter with strategic queries to sensors, the temporal logic specification is proven to be satisfied almost surely. The effectiveness of the method is demonstrated with robotic motion planning examples.

关键词： Active sensing computational game theory control formal methods temporal logic

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Design of an Efficient Algorithm to Find Pure Nash Equilibria on Strategic games

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IEEE LATIN AMERICA TRANSACTIONS 2016年第1期14卷 320-324页

作者： De Ita, G. Zacarias, F. Perez, O. Benemerita Univ Autonoma Puebla FCC Puebla Mexico

Pure Nash Equilibria are states in strategic games in which no player has motivation to change of strategy, and then the game is stabilized in such optimal states. A general objective in all strategic game is to determine if it has pure Nash equilibria, and when they exist, find such optimal points in an efficient way. A novel and efficient algorithm (a time polynomial procedure) to find Nash pure equilibria for any strategic game, independent to the number of players and the number of strategies for each player is deployed. Our algorithm requires the values of the utility function for each player and for each one of the possible states of the game. The Algorithm is an iterative process for searching the optimal states for each player (the player's Pareto) without caring about the strategies the other players are using. The algorithm compares the Pareto set of a player with the next one, in order to keep just the common Pareto states. If at the end of the process of searching for the Pareto set of the players, there exists Pareto states common to all involved players, then these states represent the pure Nash equilibria of the game, otherwise, it does not exist.

关键词： Nash Pure Equilibrium Strategic games Pareto Points computational game theory

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Addressing Behavioral Uncertainty in Security games: An Efficient Robust Strategic Solution for Defender Patrols 30

Addressing Behavioral Uncertainty in Security Games: An Effi...

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30th IEEE International Parallel and Distributed Processing Symposium (IPDPS)

作者： Nguyen, Thanh H. Sinha, Arunesh Tambe, Milind Univ Southern Calif Los Angeles CA 90007 USA

ISBN: (纸本)9781509036820

Stackelberg Security games (SSG) have been widely applied for solving real-world security problems with a significant research emphasis on modeling attackers' behaviors to handle their bounded rationality. However, access to real-world data (used for learning an accurate behavioral model) is often limited, leading to uncertainty in attacker's behaviors while modeling. This paper therefore focuses on addressing behavioral uncertainty in SSG with the following main contributions: 1) we present a new uncertainty game model that integrates uncertainty intervals into a behavioral model to capture behavioral uncertainty;and 2) based on this game model, we propose a novel robust algorithm that approximately computes the defender's optimal strategy in the worst-case scenario of uncertainty. We show that our algorithm guarantees an additive bound on its solution quality.

关键词： Behavioral modeling computational game theory Robust optimization Security games Uncertainty

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Timeability of Extensive-Form games 16

Timeability of Extensive-Form Games

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7th ACM Conference on Innovations in Theoretical Computer Science (ITCS)

作者： Jakobsen, Sune K. Sorensen, Troels B. Conitzer, Vincent Univ London Sch Elect Engn & Comp Sci Queen Mary Mile End Rd London EL 4NS England IT Univ Copenhagen Theoret Comp Sci Sect Rued Langgaards Vej 7 DK-2300 Copenhagen S Denmark Duke Univ Dept Comp Sci Box 90129 Durham NC 27708 USA

ISBN: (纸本)9781450340571

Extensive-form games constitute the standard representation scheme for games with a temporal component. But do all extensive-form games correspond to protocols that we can implement in the real world? We often rule out games with imperfect recall, which prescribe that an agent forget something that she knew before. In this paper, we show that even some games with perfect recall can be problematic to implement. Specifically, we show that if the agents have a sense of time passing (say, access to a clock), then some extensive-form games can no longer be implemented;no matter how we attempt to time the game, some information will leak to the agents that they are not supposed to have. We say such a game is not exactly timeable. We provide easy-to-check necessary and sufficient conditions for a game to be exactly timeable. Most of the technical depth of the paper concerns how to approximately time games, which we show can always be done, though it may require large amounts of time. Specifically, we show that some games require time proportional to the power tower of height proportional to the number of players, which in practice would make them untimeable. We hope to convince the reader that timeability should be a standard assumption, just as perfect recall is today. Besides the conceptual contribution to game theory, we show that timeability has implications for onion routing protocols.

关键词： computational game theory Equilibrium Computation

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