Wireless Networks under a Backoff Attack: A Game Theoretical Perspective

PubMed Central

Zazo, Santiago

2018-01-01

We study a wireless sensor network using CSMA/CA in the MAC layer under a backoff attack: some of the sensors of the network are malicious and deviate from the defined contention mechanism. We use Bianchi’s network model to study the impact of the malicious sensors on the total network throughput, showing that it causes the throughput to be unfairly distributed among sensors. We model this conflict using game theory tools, where each sensor is a player. We obtain analytical solutions and propose an algorithm, based on Regret Matching, to learn the equilibrium of the game with an arbitrary number of players. Our approach is validated via simulations, showing that our theoretical predictions adjust to reality. PMID:29385752

Distributed Power Allocation for Wireless Sensor Network Localization: A Potential Game Approach.

PubMed

Ke, Mingxing; Li, Ding; Tian, Shiwei; Zhang, Yuli; Tong, Kaixiang; Xu, Yuhua

2018-05-08

The problem of distributed power allocation in wireless sensor network (WSN) localization systems is investigated in this paper, using the game theoretic approach. Existing research focuses on the minimization of the localization errors of individual agent nodes over all anchor nodes subject to power budgets. When the service area and the distribution of target nodes are considered, finding the optimal trade-off between localization accuracy and power consumption is a new critical task. To cope with this issue, we propose a power allocation game where each anchor node minimizes the square position error bound (SPEB) of the service area penalized by its individual power. Meanwhile, it is proven that the power allocation game is an exact potential game which has one pure Nash equilibrium (NE) at least. In addition, we also prove the existence of an ϵ -equilibrium point, which is a refinement of NE and the better response dynamic approach can reach the end solution. Analytical and simulation results demonstrate that: (i) when prior distribution information is available, the proposed strategies have better localization accuracy than the uniform strategies; (ii) when prior distribution information is unknown, the performance of the proposed strategies outperforms power management strategies based on the second-order cone program (SOCP) for particular agent nodes after obtaining the estimated distribution of agent nodes. In addition, proposed strategies also provide an instructional trade-off between power consumption and localization accuracy.

A fault-tolerant small world topology control model in ad hoc networks for search and rescue

NASA Astrophysics Data System (ADS)

Tan, Mian; Fang, Ling; Wu, Yue; Zhang, Bo; Chang, Bowen; Holme, Petter; Zhao, Jing

2018-02-01

Due to their self-organized, multi-hop and distributed characteristics, ad hoc networks are useful in search and rescue. Topology control models need to be designed for energy-efficient, robust and fast communication in ad hoc networks. This paper proposes a topology control model which specializes for search and rescue-Compensation Small World-Repeated Game (CSWRG)-which integrates mobility models, constructing small world networks and a game-theoretic approach to the allocation of resources. Simulation results show that our mobility models can enhance the communication performance of the constructed small-world networks. Our strategy, based on repeated game, can suppress selfish behavior and compensate agents that encounter selfish or faulty neighbors. This model could be useful for the design of ad hoc communication networks.

An IUR evolutionary game model on the patent cooperate of Shandong China

NASA Astrophysics Data System (ADS)

Liu, Mengmeng; Ma, Yinghong; Liu, Zhiyuan; You, Xuemei

2017-06-01

Organizations of industries and university & research institutes cooperate to meet their respective needs based on social contacts, trust and share complementary resources. From the perspective of complex network together with the patent data of Shandong province in China, a novel evolutionary game model on patent cooperation network is presented. Two sides in the game model are industries and universities & research institutes respectively. The cooperation is represented by a connection when a new patent is developed together by the two sides. The optimal strategy of the evolutionary game model is quantified by the average positive cooperation probability p ¯ and the average payoff U ¯ . The feasibility of this game model is simulated on the parameters such as the knowledge spillover, the punishment, the development cost and the distribution coefficient of the benefit. The numerical simulations show that the cooperative behaviors are affected by the variation of parameters. The knowledge spillover displays different behaviors when the punishment is larger than the development cost or less than it. Those results indicate that reasonable punishment would improve the positive cooperation. The appropriate punishment will be useful to enhance the big degree nodes positively cooperate with industries and universities & research institutes. And an equitable plan for the distribution of cooperative profits is half-and-half distribution strategy for the two sides in game.

Empirical research on complex networks modeling of combat SoS based on data from real war-game, Part I: Statistical characteristics

NASA Astrophysics Data System (ADS)

Chen, Lei; Kou, Yingxin; Li, Zhanwu; Xu, An; Wu, Cheng

2018-01-01

We build a complex networks model of combat System-of-Systems (SoS) based on empirical data from a real war-game, this model is a combination of command & control (C2) subnetwork, sensors subnetwork, influencers subnetwork and logistical support subnetwork, each subnetwork has idiographic components and statistical characteristics. The C2 subnetwork is the core of whole combat SoS, it has a hierarchical structure with no modularity, of which robustness is strong enough to maintain normal operation after any two nodes is destroyed; the sensors subnetwork and influencers subnetwork are like sense organ and limbs of whole combat SoS, they are both flat modular networks of which degree distribution obey GEV distribution and power-law distribution respectively. The communication network is the combination of all subnetworks, it is an assortative Small-World network with core-periphery structure, the Intelligence & Communication Stations/Command Center integrated with C2 nodes in the first three level act as the hub nodes in communication network, and all the fourth-level C2 nodes, sensors, influencers and logistical support nodes have communication capability, they act as the periphery nodes in communication network, its degree distribution obeys exponential distribution in the beginning, Gaussian distribution in the middle, and power-law distribution in the end, and its path length obeys GEV distribution. The betweenness centrality distribution, closeness centrality distribution and eigenvector centrality are also been analyzed to measure the vulnerability of nodes.

Characterizing Crowd Participation and Productivity of Foldit Through Web Scraping

DTIC Science & Technology

2016-03-01

Berkeley Open Infrastructure for Network Computing CDF Cumulative Distribution Function CPU Central Processing Unit CSSG Crowdsourced Serious Game...computers at once can create a similar capacity. According to Anderson [6], principal investigator for the Berkeley Open Infrastructure for Network...extraterrestrial life. From this project, a software-based distributed computing platform called the Berkeley Open Infrastructure for Network Computing

Real-time strategy game training: emergence of a cognitive flexibility trait.

PubMed

Glass, Brian D; Maddox, W Todd; Love, Bradley C

2013-01-01

Training in action video games can increase the speed of perceptual processing. However, it is unknown whether video-game training can lead to broad-based changes in higher-level competencies such as cognitive flexibility, a core and neurally distributed component of cognition. To determine whether video gaming can enhance cognitive flexibility and, if so, why these changes occur, the current study compares two versions of a real-time strategy (RTS) game. Using a meta-analytic Bayes factor approach, we found that the gaming condition that emphasized maintenance and rapid switching between multiple information and action sources led to a large increase in cognitive flexibility as measured by a wide array of non-video gaming tasks. Theoretically, the results suggest that the distributed brain networks supporting cognitive flexibility can be tuned by engrossing video game experience that stresses maintenance and rapid manipulation of multiple information sources. Practically, these results suggest avenues for increasing cognitive function.

Real-Time Strategy Game Training: Emergence of a Cognitive Flexibility Trait

PubMed Central

Glass, Brian D.; Maddox, W. Todd; Love, Bradley C.

2013-01-01

Training in action video games can increase the speed of perceptual processing. However, it is unknown whether video-game training can lead to broad-based changes in higher-level competencies such as cognitive flexibility, a core and neurally distributed component of cognition. To determine whether video gaming can enhance cognitive flexibility and, if so, why these changes occur, the current study compares two versions of a real-time strategy (RTS) game. Using a meta-analytic Bayes factor approach, we found that the gaming condition that emphasized maintenance and rapid switching between multiple information and action sources led to a large increase in cognitive flexibility as measured by a wide array of non-video gaming tasks. Theoretically, the results suggest that the distributed brain networks supporting cognitive flexibility can be tuned by engrossing video game experience that stresses maintenance and rapid manipulation of multiple information sources. Practically, these results suggest avenues for increasing cognitive function. PMID:23950921

Effect of network topology on the evolutionary ultimatum game based on the net-profit decision

NASA Astrophysics Data System (ADS)

Ye, Shun-Qiang; Wang, Lu; Jones, Michael C.; Ye, Ye; Wang, Meng; Xie, Neng-Gang

2016-04-01

The ubiquity of altruist behavior amongst humans has long been a significant puzzle in the social sciences. Ultimatum game has proved to be a useful tool for explaining altruistic behavior among selfish individuals. In an ultimatum game where alternating roles exist, we suppose that players make their decisions based on the net profit of their own. In this paper, we specify a player's strategy with two parameters: offer level α ∈ [ 0,1) and net profit acceptance level β ∈ [ - 1,1). By Monte Carlo simulation, we analyze separately the effect of the size of the neighborhood, the small-world property and the heterogeneity of the degree distributions of the networks. Results show that compared with results observed for homogeneous networks, heterogeneous networks lead to more rational outcomes. Moreover, network structure has no effect on the evolution of kindness level, so moderate kindness is adaptable to any social groups and organizations.

Spatially correlated heterogeneous aspirations to enhance network reciprocity

NASA Astrophysics Data System (ADS)

Tanimoto, Jun; Nakata, Makoto; Hagishima, Aya; Ikegaya, Naoki

2012-02-01

Perc & Wang demonstrated that aspiring to be the fittest under conditions of pairwise strategy updating enhances network reciprocity in structured populations playing 2×2 Prisoner's Dilemma games (Z. Wang, M. Perc, Aspiring to the fittest and promoted of cooperation in the Prisoner's Dilemma game, Physical Review E 82 (2010) 021115; M. Perc, Z. Wang, Heterogeneous aspiration promotes cooperation in the Prisoner's Dilemma game, PLOS one 5 (12) (2010) e15117). Through numerical simulations, this paper shows that network reciprocity is even greater if heterogeneous aspirations are imposed. We also suggest why heterogeneous aspiration fosters network reciprocity. It distributes strategy updating speed among agents in a manner that fortifies the initially allocated cooperators' clusters against invasion. This finding prompted us to further enhance the usual heterogeneous aspiration cases for heterogeneous network topologies. We find that a negative correlation between degree and aspiration level does extend cooperation among heterogeneously structured agents.

Optimizing Cellular Networks Enabled with Renewal Energy via Strategic Learning.

PubMed

Sohn, Insoo; Liu, Huaping; Ansari, Nirwan

2015-01-01

An important issue in the cellular industry is the rising energy cost and carbon footprint due to the rapid expansion of the cellular infrastructure. Greening cellular networks has thus attracted attention. Among the promising green cellular network techniques, the renewable energy-powered cellular network has drawn increasing attention as a critical element towards reducing carbon emissions due to massive energy consumption in the base stations deployed in cellular networks. Game theory is a branch of mathematics that is used to evaluate and optimize systems with multiple players with conflicting objectives and has been successfully used to solve various problems in cellular networks. In this paper, we model the green energy utilization and power consumption optimization problem of a green cellular network as a pilot power selection strategic game and propose a novel distributed algorithm based on a strategic learning method. The simulation results indicate that the proposed algorithm achieves correlated equilibrium of the pilot power selection game, resulting in optimum green energy utilization and power consumption reduction.

Game theoretic sensor management for target tracking

NASA Astrophysics Data System (ADS)

Shen, Dan; Chen, Genshe; Blasch, Erik; Pham, Khanh; Douville, Philip; Yang, Chun; Kadar, Ivan

2010-04-01

This paper develops and evaluates a game-theoretic approach to distributed sensor-network management for target tracking via sensor-based negotiation. We present a distributed sensor-based negotiation game model for sensor management for multi-sensor multi-target tacking situations. In our negotiation framework, each negotiation agent represents a sensor and each sensor maximizes their utility using a game approach. The greediness of each sensor is limited by the fact that the sensor-to-target assignment efficiency will decrease if too many sensor resources are assigned to a same target. It is similar to the market concept in real world, such as agreements between buyers and sellers in an auction market. Sensors are willing to switch targets so that they can obtain their highest utility and the most efficient way of applying their resources. Our sub-game perfect equilibrium-based negotiation strategies dynamically and distributedly assign sensors to targets. Numerical simulations are performed to demonstrate our sensor-based negotiation approach for distributed sensor management.

Cyber Security Research Frameworks For Coevolutionary Network Defense

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rush, George D.; Tauritz, Daniel Remy

Several architectures have been created for developing and testing systems used in network security, but most are meant to provide a platform for running cyber security experiments as opposed to automating experiment processes. In the first paper, we propose a framework termed Distributed Cyber Security Automation Framework for Experiments (DCAFE) that enables experiment automation and control in a distributed environment. Predictive analysis of adversaries is another thorny issue in cyber security. Game theory can be used to mathematically analyze adversary models, but its scalability limitations restrict its use. Computational game theory allows us to scale classical game theory to larger,more » more complex systems. In the second paper, we propose a framework termed Coevolutionary Agent-based Network Defense Lightweight Event System (CANDLES) that can coevolve attacker and defender agent strategies and capabilities and evaluate potential solutions with a custom network defense simulation. The third paper is a continuation of the CANDLES project in which we rewrote key parts of the framework. Attackers and defenders have been redesigned to evolve pure strategy, and a new network security simulation is devised which specifies network architecture and adds a temporal aspect. We also add a hill climber algorithm to evaluate the search space and justify the use of a coevolutionary algorithm.« less

Evolution of Cooperation in Social Dilemmas on Complex Networks

PubMed Central

Iyer, Swami; Killingback, Timothy

2016-01-01

Cooperation in social dilemmas is essential for the functioning of systems at multiple levels of complexity, from the simplest biological organisms to the most sophisticated human societies. Cooperation, although widespread, is fundamentally challenging to explain evolutionarily, since natural selection typically favors selfish behavior which is not socially optimal. Here we study the evolution of cooperation in three exemplars of key social dilemmas, representing the prisoner’s dilemma, hawk-dove and coordination classes of games, in structured populations defined by complex networks. Using individual-based simulations of the games on model and empirical networks, we give a detailed comparative study of the effects of the structural properties of a network, such as its average degree, variance in degree distribution, clustering coefficient, and assortativity coefficient, on the promotion of cooperative behavior in all three classes of games. PMID:26928428

Multi-Objective Optimization for Trustworthy Tactical Networks: A Survey and Insights

DTIC Science & Technology

2013-06-01

existing data sources, gathering and maintaining the data needed , and completing and reviewing the collection of information. Send comments regarding...problems: using repeated cooperative games [12], hedonic games [25], and nontransferable utility cooperative games [27]. It should be noted that trust...examined an optimal task allocation problem in a distributed computing system where program modules need to be allocated to different processors to

A Game Theoretic Approach for Balancing Energy Consumption in Clustered Wireless Sensor Networks.

PubMed

Yang, Liu; Lu, Yinzhi; Xiong, Lian; Tao, Yang; Zhong, Yuanchang

2017-11-17

Clustering is an effective topology control method in wireless sensor networks (WSNs), since it can enhance the network lifetime and scalability. To prolong the network lifetime in clustered WSNs, an efficient cluster head (CH) optimization policy is essential to distribute the energy among sensor nodes. Recently, game theory has been introduced to model clustering. Each sensor node is considered as a rational and selfish player which will play a clustering game with an equilibrium strategy. Then it decides whether to act as the CH according to this strategy for a tradeoff between providing required services and energy conservation. However, how to get the equilibrium strategy while maximizing the payoff of sensor nodes has rarely been addressed to date. In this paper, we present a game theoretic approach for balancing energy consumption in clustered WSNs. With our novel payoff function, realistic sensor behaviors can be captured well. The energy heterogeneity of nodes is considered by incorporating a penalty mechanism in the payoff function, so the nodes with more energy will compete for CHs more actively. We have obtained the Nash equilibrium (NE) strategy of the clustering game through convex optimization. Specifically, each sensor node can achieve its own maximal payoff when it makes the decision according to this strategy. Through plenty of simulations, our proposed game theoretic clustering is proved to have a good energy balancing performance and consequently the network lifetime is greatly enhanced.

Power allocation for target detection in radar networks based on low probability of intercept: A cooperative game theoretical strategy

NASA Astrophysics Data System (ADS)

Shi, Chenguang; Salous, Sana; Wang, Fei; Zhou, Jianjiang

2017-08-01

Distributed radar network systems have been shown to have many unique features. Due to their advantage of signal and spatial diversities, radar networks are attractive for target detection. In practice, the netted radars in radar networks are supposed to maximize their transmit power to achieve better detection performance, which may be in contradiction with low probability of intercept (LPI). Therefore, this paper investigates the problem of adaptive power allocation for radar networks in a cooperative game-theoretic framework such that the LPI performance can be improved. Taking into consideration both the transmit power constraints and the minimum signal to interference plus noise ratio (SINR) requirement of each radar, a cooperative Nash bargaining power allocation game based on LPI is formulated, whose objective is to minimize the total transmit power by optimizing the power allocation in radar networks. First, a novel SINR-based network utility function is defined and utilized as a metric to evaluate power allocation. Then, with the well-designed network utility function, the existence and uniqueness of the Nash bargaining solution are proved analytically. Finally, an iterative Nash bargaining algorithm is developed that converges quickly to a Pareto optimal equilibrium for the cooperative game. Numerical simulations and theoretic analysis are provided to evaluate the effectiveness of the proposed algorithm.

Self-Coexistence among IEEE 802.22 Networks: Distributed Allocation of Power and Channel

PubMed Central

Sakin, Sayef Azad; Alamri, Atif; Tran, Nguyen H.

2017-01-01

Ensuring self-coexistence among IEEE 802.22 networks is a challenging problem owing to opportunistic access of incumbent-free radio resources by users in co-located networks. In this study, we propose a fully-distributed non-cooperative approach to ensure self-coexistence in downlink channels of IEEE 802.22 networks. We formulate the self-coexistence problem as a mixed-integer non-linear optimization problem for maximizing the network data rate, which is an NP-hard one. This work explores a sub-optimal solution by dividing the optimization problem into downlink channel allocation and power assignment sub-problems. Considering fairness, quality of service and minimum interference for customer-premises-equipment, we also develop a greedy algorithm for channel allocation and a non-cooperative game-theoretic framework for near-optimal power allocation. The base stations of networks are treated as players in a game, where they try to increase spectrum utilization by controlling power and reaching a Nash equilibrium point. We further develop a utility function for the game to increase the data rate by minimizing the transmission power and, subsequently, the interference from neighboring networks. A theoretical proof of the uniqueness and existence of the Nash equilibrium has been presented. Performance improvements in terms of data-rate with a degree of fairness compared to a cooperative branch-and-bound-based algorithm and a non-cooperative greedy approach have been shown through simulation studies. PMID:29215591

Self-Coexistence among IEEE 802.22 Networks: Distributed Allocation of Power and Channel.

PubMed

Sakin, Sayef Azad; Razzaque, Md Abdur; Hassan, Mohammad Mehedi; Alamri, Atif; Tran, Nguyen H; Fortino, Giancarlo

2017-12-07

Ensuring self-coexistence among IEEE 802.22 networks is a challenging problem owing to opportunistic access of incumbent-free radio resources by users in co-located networks. In this study, we propose a fully-distributed non-cooperative approach to ensure self-coexistence in downlink channels of IEEE 802.22 networks. We formulate the self-coexistence problem as a mixed-integer non-linear optimization problem for maximizing the network data rate, which is an NP-hard one. This work explores a sub-optimal solution by dividing the optimization problem into downlink channel allocation and power assignment sub-problems. Considering fairness, quality of service and minimum interference for customer-premises-equipment, we also develop a greedy algorithm for channel allocation and a non-cooperative game-theoretic framework for near-optimal power allocation. The base stations of networks are treated as players in a game, where they try to increase spectrum utilization by controlling power and reaching a Nash equilibrium point. We further develop a utility function for the game to increase the data rate by minimizing the transmission power and, subsequently, the interference from neighboring networks. A theoretical proof of the uniqueness and existence of the Nash equilibrium has been presented. Performance improvements in terms of data-rate with a degree of fairness compared to a cooperative branch-and-bound-based algorithm and a non-cooperative greedy approach have been shown through simulation studies.

Bipartite graphs as models of population structures in evolutionary multiplayer games.

PubMed

Peña, Jorge; Rochat, Yannick

2012-01-01

By combining evolutionary game theory and graph theory, "games on graphs" study the evolutionary dynamics of frequency-dependent selection in population structures modeled as geographical or social networks. Networks are usually represented by means of unipartite graphs, and social interactions by two-person games such as the famous prisoner's dilemma. Unipartite graphs have also been used for modeling interactions going beyond pairwise interactions. In this paper, we argue that bipartite graphs are a better alternative to unipartite graphs for describing population structures in evolutionary multiplayer games. To illustrate this point, we make use of bipartite graphs to investigate, by means of computer simulations, the evolution of cooperation under the conventional and the distributed N-person prisoner's dilemma. We show that several implicit assumptions arising from the standard approach based on unipartite graphs (such as the definition of replacement neighborhoods, the intertwining of individual and group diversity, and the large overlap of interaction neighborhoods) can have a large impact on the resulting evolutionary dynamics. Our work provides a clear example of the importance of construction procedures in games on graphs, of the suitability of bigraphs and hypergraphs for computational modeling, and of the importance of concepts from social network analysis such as centrality, centralization and bipartite clustering for the understanding of dynamical processes occurring on networked population structures.

Analysis of the "naming game" with learning errors in communications.

PubMed

Lou, Yang; Chen, Guanrong

2015-07-16

Naming game simulates the process of naming an objective by a population of agents organized in a certain communication network. By pair-wise iterative interactions, the population reaches consensus asymptotically. We study naming game with communication errors during pair-wise conversations, with error rates in a uniform probability distribution. First, a model of naming game with learning errors in communications (NGLE) is proposed. Then, a strategy for agents to prevent learning errors is suggested. To that end, three typical topologies of communication networks, namely random-graph, small-world and scale-free networks, are employed to investigate the effects of various learning errors. Simulation results on these models show that 1) learning errors slightly affect the convergence speed but distinctively increase the requirement for memory of each agent during lexicon propagation; 2) the maximum number of different words held by the population increases linearly as the error rate increases; 3) without applying any strategy to eliminate learning errors, there is a threshold of the learning errors which impairs the convergence. The new findings may help to better understand the role of learning errors in naming game as well as in human language development from a network science perspective.

Game-Theoretical Design of an Adaptive Distributed Dissemination Protocol for VANETs.

PubMed

Iza-Paredes, Cristhian; Mezher, Ahmad Mohamad; Aguilar Igartua, Mónica; Forné, Jordi

2018-01-19

Road safety applications envisaged for Vehicular Ad Hoc Networks (VANETs) depend largely on the dissemination of warning messages to deliver information to concerned vehicles. The intended applications, as well as some inherent VANET characteristics, make data dissemination an essential service and a challenging task in this kind of networks. This work lays out a decentralized stochastic solution for the data dissemination problem through two game-theoretical mechanisms. Given the non-stationarity induced by a highly dynamic topology, diverse network densities, and intermittent connectivity, a solution for the formulated game requires an adaptive procedure able to exploit the environment changes. Extensive simulations reveal that our proposal excels in terms of number of transmissions, lower end-to-end delay and reduced overhead while maintaining high delivery ratio, compared to other proposals.

Game-Theoretical Design of an Adaptive Distributed Dissemination Protocol for VANETs

PubMed Central

Mezher, Ahmad Mohamad; Aguilar Igartua, Mónica

2018-01-01

Road safety applications envisaged for Vehicular Ad Hoc Networks (VANETs) depend largely on the dissemination of warning messages to deliver information to concerned vehicles. The intended applications, as well as some inherent VANET characteristics, make data dissemination an essential service and a challenging task in this kind of networks. This work lays out a decentralized stochastic solution for the data dissemination problem through two game-theoretical mechanisms. Given the non-stationarity induced by a highly dynamic topology, diverse network densities, and intermittent connectivity, a solution for the formulated game requires an adaptive procedure able to exploit the environment changes. Extensive simulations reveal that our proposal excels in terms of number of transmissions, lower end-to-end delay and reduced overhead while maintaining high delivery ratio, compared to other proposals. PMID:29351255

A Game Theoretic Approach for Balancing Energy Consumption in Clustered Wireless Sensor Networks

PubMed Central

Lu, Yinzhi; Xiong, Lian; Tao, Yang; Zhong, Yuanchang

2017-01-01

Clustering is an effective topology control method in wireless sensor networks (WSNs), since it can enhance the network lifetime and scalability. To prolong the network lifetime in clustered WSNs, an efficient cluster head (CH) optimization policy is essential to distribute the energy among sensor nodes. Recently, game theory has been introduced to model clustering. Each sensor node is considered as a rational and selfish player which will play a clustering game with an equilibrium strategy. Then it decides whether to act as the CH according to this strategy for a tradeoff between providing required services and energy conservation. However, how to get the equilibrium strategy while maximizing the payoff of sensor nodes has rarely been addressed to date. In this paper, we present a game theoretic approach for balancing energy consumption in clustered WSNs. With our novel payoff function, realistic sensor behaviors can be captured well. The energy heterogeneity of nodes is considered by incorporating a penalty mechanism in the payoff function, so the nodes with more energy will compete for CHs more actively. We have obtained the Nash equilibrium (NE) strategy of the clustering game through convex optimization. Specifically, each sensor node can achieve its own maximal payoff when it makes the decision according to this strategy. Through plenty of simulations, our proposed game theoretic clustering is proved to have a good energy balancing performance and consequently the network lifetime is greatly enhanced. PMID:29149075

Bipartite Graphs as Models of Population Structures in Evolutionary Multiplayer Games

PubMed Central

Peña, Jorge; Rochat, Yannick

2012-01-01

By combining evolutionary game theory and graph theory, “games on graphs” study the evolutionary dynamics of frequency-dependent selection in population structures modeled as geographical or social networks. Networks are usually represented by means of unipartite graphs, and social interactions by two-person games such as the famous prisoner’s dilemma. Unipartite graphs have also been used for modeling interactions going beyond pairwise interactions. In this paper, we argue that bipartite graphs are a better alternative to unipartite graphs for describing population structures in evolutionary multiplayer games. To illustrate this point, we make use of bipartite graphs to investigate, by means of computer simulations, the evolution of cooperation under the conventional and the distributed N-person prisoner’s dilemma. We show that several implicit assumptions arising from the standard approach based on unipartite graphs (such as the definition of replacement neighborhoods, the intertwining of individual and group diversity, and the large overlap of interaction neighborhoods) can have a large impact on the resulting evolutionary dynamics. Our work provides a clear example of the importance of construction procedures in games on graphs, of the suitability of bigraphs and hypergraphs for computational modeling, and of the importance of concepts from social network analysis such as centrality, centralization and bipartite clustering for the understanding of dynamical processes occurring on networked population structures. PMID:22970237

Naming Game with Multiple Hearers

NASA Astrophysics Data System (ADS)

Li, Bing; Chen, Guanrong; Chow, Tommy W. S.

2013-05-01

A new model called Naming Game with Multiple Hearers (NGMH) is proposed in this paper. A naming game over a population of individuals aims to reach consensus on the name of an object through pair-wise local interactions among all the individuals. The proposed NGMH model describes the learning process of a new word, in a population with one speaker and multiple hearers, at each interaction towards convergence. The characteristics of NGMH are examined on three types of network topologies, namely ER random-graph network, WS small-world network, and BA scale-free network. Comparative analysis on the convergence time is performed, revealing that the topology with a larger average (node) degree can reach consensus faster than the others over the same population. It is found that, for a homogeneous network, the average degree is the limiting value of the number of hearers, which reduces the individual ability of learning new words, consequently decreasing the convergence time; for a scale-free network, this limiting value is the deviation of the average degree. It is also found that a network with a larger clustering coefficient takes longer time to converge; especially a small-word network with smallest rewiring possibility takes longest time to reach convergence. As more new nodes are being added to scale-free networks with different degree distributions, their convergence time appears to be robust against the network-size variation. Most new findings reported in this paper are different from that of the single-speaker/single-hearer naming games documented in the literature.

Competitive energy consumption under transmission constraints in a multi-supplier power grid system

NASA Astrophysics Data System (ADS)

Popov, Ivan; Krylatov, Alexander; Zakharov, Victor; Ivanov, Dmitry

2017-04-01

Power grid architectures need to be revised in order to manage the increasing number of producers and, more generally, the decentralisation of energy production and distribution. In this work, we describe a multi-supplier multi-consumer congestion model of a power grid, where the costs of consumers depend on the congestion in nodes and arcs of the power supply network. The consumer goal is both to meet their energy demand and to minimise the costs. We show that the methods of non-atomic routing can be applied in this model in order to describe current distribution in the network. We formulate a consumer cost minimisation game for this setting, and discuss the challenges arising in equilibrium search for this game.

A Coalitional Game for Distributed Inference in Sensor Networks With Dependent Observations

NASA Astrophysics Data System (ADS)

He, Hao; Varshney, Pramod K.

2016-04-01

We consider the problem of collaborative inference in a sensor network with heterogeneous and statistically dependent sensor observations. Each sensor aims to maximize its inference performance by forming a coalition with other sensors and sharing information within the coalition. It is proved that the inference performance is a nondecreasing function of the coalition size. However, in an energy constrained network, the energy consumption of inter-sensor communication also increases with increasing coalition size, which discourages the formation of the grand coalition (the set of all sensors). In this paper, the formation of non-overlapping coalitions with statistically dependent sensors is investigated under a specific communication constraint. We apply a game theoretical approach to fully explore and utilize the information contained in the spatial dependence among sensors to maximize individual sensor performance. Before formulating the distributed inference problem as a coalition formation game, we first quantify the gain and loss in forming a coalition by introducing the concepts of diversity gain and redundancy loss for both estimation and detection problems. These definitions, enabled by the statistical theory of copulas, allow us to characterize the influence of statistical dependence among sensor observations on inference performance. An iterative algorithm based on merge-and-split operations is proposed for the solution and the stability of the proposed algorithm is analyzed. Numerical results are provided to demonstrate the superiority of our proposed game theoretical approach.

Enabling Controlling Complex Networks with Local Topological Information.

PubMed

Li, Guoqi; Deng, Lei; Xiao, Gaoxi; Tang, Pei; Wen, Changyun; Hu, Wuhua; Pei, Jing; Shi, Luping; Stanley, H Eugene

2018-03-15

Complex networks characterize the nature of internal/external interactions in real-world systems including social, economic, biological, ecological, and technological networks. Two issues keep as obstacles to fulfilling control of large-scale networks: structural controllability which describes the ability to guide a dynamical system from any initial state to any desired final state in finite time, with a suitable choice of inputs; and optimal control, which is a typical control approach to minimize the cost for driving the network to a predefined state with a given number of control inputs. For large complex networks without global information of network topology, both problems remain essentially open. Here we combine graph theory and control theory for tackling the two problems in one go, using only local network topology information. For the structural controllability problem, a distributed local-game matching method is proposed, where every node plays a simple Bayesian game with local information and local interactions with adjacent nodes, ensuring a suboptimal solution at a linear complexity. Starring from any structural controllability solution, a minimizing longest control path method can efficiently reach a good solution for the optimal control in large networks. Our results provide solutions for distributed complex network control and demonstrate a way to link the structural controllability and optimal control together.

Propagation, cascades, and agreement dynamics in complex communication and social networks

NASA Astrophysics Data System (ADS)

Lu, Qiming

Many modern and important technological, social, information and infrastructure systems can be viewed as complex systems with a large number of interacting components. Models of complex networks and dynamical interactions, as well as their applications are of fundamental interests in many aspects. Here, several stylized models of multiplex propagation and opinion dynamics are investigated on complex and empirical social networks. We first investigate cascade dynamics in threshold-controlled (multiplex) propagation on random geometric networks. We find that such local dynamics can serve as an efficient, robust, and reliable prototypical activation protocol in sensor networks in responding to various alarm scenarios. We also consider the same dynamics on a modified network by adding a few long-range communication links, resulting in a small-world network. We find that such construction can further enhance and optimize the speed of the network's response, while keeping energy consumption at a manageable level. We also investigate a prototypical agent-based model, the Naming Game, on two-dimensional random geometric networks. The Naming Game [A. Baronchelli et al., J. Stat. Mech.: Theory Exp. (2006) P06014.] is a minimal model, employing local communications that captures the emergence of shared communication schemes (languages) in a population of autonomous semiotic agents. Implementing the Naming Games with local broadcasts on random geometric graphs, serves as a model for agreement dynamics in large-scale, autonomously operating wireless sensor networks. Further, it captures essential features of the scaling properties of the agreement process for spatially-embedded autonomous agents. Among the relevant observables capturing the temporal properties of the agreement process, we investigate the cluster-size distribution and the distribution of the agreement times, both exhibiting dynamic scaling. We also present results for the case when a small density of long-range communication links are added on top of the random geometric graph, resulting in a "small-world"-like network and yielding a significantly reduced time to reach global agreement. We construct a finite-size scaling analysis for the agreement times in this case. When applying the model of Naming Game on empirical social networks, this stylized agent-based model captures essential features of agreement dynamics in a network of autonomous agents, corresponding to the development of shared classification schemes in a network of artificial agents or opinion spreading and social dynamics in social networks. Our study focuses on the impact that communities in the underlying social graphs have on the outcome of the agreement process. We find that networks with strong community structure hinder the system from reaching global agreement; the evolution of the Naming Game in these networks maintains clusters of coexisting opinions indefinitely. Further, we investigate agent-based network strategies to facilitate convergence to global consensus.

Analysis of the “naming game” with learning errors in communications

NASA Astrophysics Data System (ADS)

Lou, Yang; Chen, Guanrong

2015-07-01

Naming game simulates the process of naming an objective by a population of agents organized in a certain communication network. By pair-wise iterative interactions, the population reaches consensus asymptotically. We study naming game with communication errors during pair-wise conversations, with error rates in a uniform probability distribution. First, a model of naming game with learning errors in communications (NGLE) is proposed. Then, a strategy for agents to prevent learning errors is suggested. To that end, three typical topologies of communication networks, namely random-graph, small-world and scale-free networks, are employed to investigate the effects of various learning errors. Simulation results on these models show that 1) learning errors slightly affect the convergence speed but distinctively increase the requirement for memory of each agent during lexicon propagation; 2) the maximum number of different words held by the population increases linearly as the error rate increases; 3) without applying any strategy to eliminate learning errors, there is a threshold of the learning errors which impairs the convergence. The new findings may help to better understand the role of learning errors in naming game as well as in human language development from a network science perspective.

Impact of deterministic and stochastic updates on network reciprocity in the prisoner's dilemma game

NASA Astrophysics Data System (ADS)

Tanimoto, Jun

2014-08-01

In 2 × 2 prisoner's dilemma games, network reciprocity is one mechanism for adding social viscosity, which leads to cooperative equilibrium. This study introduced an intriguing framework for the strategy update rule that allows any combination of a purely deterministic method, imitation max (IM), and a purely probabilistic one, pairwise Fermi (Fermi-PW). A series of simulations covering the whole range from IM to Fermi-PW reveals that, as a general tendency, the larger fractions of stochastic updating reduce network reciprocity, so long as the underlying lattice contains no noise in the degree of distribution. However, a small amount of stochastic flavor added to an otherwise perfectly deterministic update rule was actually found to enhance network reciprocity. This occurs because a subtle stochastic effect in the update rule improves the evolutionary trail in games having more stag-hunt-type dilemmas, although the same stochastic effect degenerates evolutionary trails in games having more chicken-type dilemmas. We explain these effects by dividing evolutionary trails into the enduring and expanding periods defined by Shigaki et al. [Phys. Rev. E 86, 031141 (2012), 10.1103/PhysRevE.86.031141].

Simulating the wealth distribution with a Richest-Following strategy on scale-free network

NASA Astrophysics Data System (ADS)

Hu, Mao-Bin; Jiang, Rui; Wu, Qing-Song; Wu, Yong-Hong

2007-07-01

In this paper, we investigate the wealth distribution with agents playing evolutionary games on a scale-free social network adopting the Richest-Following strategy. Pareto's power-law distribution (1897) of wealth is demonstrated with power factor in agreement with that of US or Japan. Moreover, the agent's personal wealth is proportional to its number of contacts (connectivity), and this leads to the phenomenon that the rich gets richer and the poor gets relatively poorer, which agrees with the Matthew Effect.

Structure constrained by metadata in networks of chess players.

PubMed

Almeira, Nahuel; Schaigorodsky, Ana L; Perotti, Juan I; Billoni, Orlando V

2017-11-09

Chess is an emblematic sport that stands out because of its age, popularity and complexity. It has served to study human behavior from the perspective of a wide number of disciplines, from cognitive skills such as memory and learning, to aspects like innovation and decision-making. Given that an extensive documentation of chess games played throughout history is available, it is possible to perform detailed and statistically significant studies about this sport. Here we use one of the most extensive chess databases in the world to construct two networks of chess players. One of the networks includes games that were played over-the-board and the other contains games played on the Internet. We study the main topological characteristics of the networks, such as degree distribution and correlations, transitivity and community structure. We complement the structural analysis by incorporating players' level of play as node metadata. Although both networks are topologically different, we show that in both cases players gather in communities according to their expertise and that an emergent rich-club structure, composed by the top-rated players, is also present.

Cyber War Game in Temporal Networks

PubMed Central

Cho, Jin-Hee; Gao, Jianxi

2016-01-01

In a cyber war game where a network is fully distributed and characterized by resource constraints and high dynamics, attackers or defenders often face a situation that may require optimal strategies to win the game with minimum effort. Given the system goal states of attackers and defenders, we study what strategies attackers or defenders can take to reach their respective system goal state (i.e., winning system state) with minimum resource consumption. However, due to the dynamics of a network caused by a node’s mobility, failure or its resource depletion over time or action(s), this optimization problem becomes NP-complete. We propose two heuristic strategies in a greedy manner based on a node’s two characteristics: resource level and influence based on k-hop reachability. We analyze complexity and optimality of each algorithm compared to optimal solutions for a small-scale static network. Further, we conduct a comprehensive experimental study for a large-scale temporal network to investigate best strategies, given a different environmental setting of network temporality and density. We demonstrate the performance of each strategy under various scenarios of attacker/defender strategies in terms of win probability, resource consumption, and system vulnerability. PMID:26859840

Effects of behavioral patterns and network topology structures on Parrondo’s paradox

PubMed Central

Ye, Ye; Cheong, Kang Hao; Cen, Yu-wan; Xie, Neng-gang

2016-01-01

A multi-agent Parrondo’s model based on complex networks is used in the current study. For Parrondo’s game A, the individual interaction can be categorized into five types of behavioral patterns: the Matthew effect, harmony, cooperation, poor-competition-rich-cooperation and a random mode. The parameter space of Parrondo’s paradox pertaining to each behavioral pattern, and the gradual change of the parameter space from a two-dimensional lattice to a random network and from a random network to a scale-free network was analyzed. The simulation results suggest that the size of the region of the parameter space that elicits Parrondo’s paradox is positively correlated with the heterogeneity of the degree distribution of the network. For two distinct sets of probability parameters, the microcosmic reasons underlying the occurrence of the paradox under the scale-free network are elaborated. Common interaction mechanisms of the asymmetric structure of game B, behavioral patterns and network topology are also revealed. PMID:27845430

Effects of behavioral patterns and network topology structures on Parrondo’s paradox

NASA Astrophysics Data System (ADS)

Ye, Ye; Cheong, Kang Hao; Cen, Yu-Wan; Xie, Neng-Gang

2016-11-01

A multi-agent Parrondo’s model based on complex networks is used in the current study. For Parrondo’s game A, the individual interaction can be categorized into five types of behavioral patterns: the Matthew effect, harmony, cooperation, poor-competition-rich-cooperation and a random mode. The parameter space of Parrondo’s paradox pertaining to each behavioral pattern, and the gradual change of the parameter space from a two-dimensional lattice to a random network and from a random network to a scale-free network was analyzed. The simulation results suggest that the size of the region of the parameter space that elicits Parrondo’s paradox is positively correlated with the heterogeneity of the degree distribution of the network. For two distinct sets of probability parameters, the microcosmic reasons underlying the occurrence of the paradox under the scale-free network are elaborated. Common interaction mechanisms of the asymmetric structure of game B, behavioral patterns and network topology are also revealed.

Basketball Teams as Strategic Networks

PubMed Central

Fewell, Jennifer H.; Armbruster, Dieter; Ingraham, John; Petersen, Alexander; Waters, James S.

2012-01-01

We asked how team dynamics can be captured in relation to function by considering games in the first round of the NBA 2010 play-offs as networks. Defining players as nodes and ball movements as links, we analyzed the network properties of degree centrality, clustering, entropy and flow centrality across teams and positions, to characterize the game from a network perspective and to determine whether we can assess differences in team offensive strategy by their network properties. The compiled network structure across teams reflected a fundamental attribute of basketball strategy. They primarily showed a centralized ball distribution pattern with the point guard in a leadership role. However, individual play-off teams showed variation in their relative involvement of other players/positions in ball distribution, reflected quantitatively by differences in clustering and degree centrality. We also characterized two potential alternate offensive strategies by associated variation in network structure: (1) whether teams consistently moved the ball towards their shooting specialists, measured as “uphill/downhill” flux, and (2) whether they distributed the ball in a way that reduced predictability, measured as team entropy. These network metrics quantified different aspects of team strategy, with no single metric wholly predictive of success. However, in the context of the 2010 play-offs, the values of clustering (connectedness across players) and network entropy (unpredictability of ball movement) had the most consistent association with team advancement. Our analyses demonstrate the utility of network approaches in quantifying team strategy and show that testable hypotheses can be evaluated using this approach. These analyses also highlight the richness of basketball networks as a dataset for exploring the relationships between network structure and dynamics with team organization and effectiveness. PMID:23139744

Basketball teams as strategic networks.

PubMed

Fewell, Jennifer H; Armbruster, Dieter; Ingraham, John; Petersen, Alexander; Waters, James S

2012-01-01

We asked how team dynamics can be captured in relation to function by considering games in the first round of the NBA 2010 play-offs as networks. Defining players as nodes and ball movements as links, we analyzed the network properties of degree centrality, clustering, entropy and flow centrality across teams and positions, to characterize the game from a network perspective and to determine whether we can assess differences in team offensive strategy by their network properties. The compiled network structure across teams reflected a fundamental attribute of basketball strategy. They primarily showed a centralized ball distribution pattern with the point guard in a leadership role. However, individual play-off teams showed variation in their relative involvement of other players/positions in ball distribution, reflected quantitatively by differences in clustering and degree centrality. We also characterized two potential alternate offensive strategies by associated variation in network structure: (1) whether teams consistently moved the ball towards their shooting specialists, measured as "uphill/downhill" flux, and (2) whether they distributed the ball in a way that reduced predictability, measured as team entropy. These network metrics quantified different aspects of team strategy, with no single metric wholly predictive of success. However, in the context of the 2010 play-offs, the values of clustering (connectedness across players) and network entropy (unpredictability of ball movement) had the most consistent association with team advancement. Our analyses demonstrate the utility of network approaches in quantifying team strategy and show that testable hypotheses can be evaluated using this approach. These analyses also highlight the richness of basketball networks as a dataset for exploring the relationships between network structure and dynamics with team organization and effectiveness.

Concurrent Transmission Based on Channel Quality in Ad Hoc Networks: A Game Theoretic Approach

NASA Astrophysics Data System (ADS)

Chen, Chen; Gao, Xinbo; Li, Xiaoji; Pei, Qingqi

In this paper, a decentralized concurrent transmission strategy in shared channel in Ad Hoc networks is proposed based on game theory. Firstly, a static concurrent transmissions game is used to determine the candidates for transmitting by channel quality threshold and to maximize the overall throughput with consideration of channel quality variation. To achieve NES (Nash Equilibrium Solution), the selfish behaviors of node to attempt to improve the channel gain unilaterally are evaluated. Therefore, this game allows each node to be distributed and to decide whether to transmit concurrently with others or not depending on NES. Secondly, as there are always some nodes with lower channel gain than NES, which are defined as hunger nodes in this paper, a hunger suppression scheme is proposed by adjusting the price function with interferences reservation and forward relay, to fairly give hunger nodes transmission opportunities. Finally, inspired by stock trading, a dynamic concurrent transmission threshold determination scheme is implemented to make the static game practical. Numerical results show that the proposed scheme is feasible to increase concurrent transmission opportunities for active nodes, and at the same time, the number of hunger nodes is greatly reduced with the least increase of threshold by interferences reservation. Also, the good performance on network goodput of the proposed model can be seen from the results.

Optimal Power Control in Wireless Powered Sensor Networks: A Dynamic Game-Based Approach

PubMed Central

Xu, Haitao; Guo, Chao; Zhang, Long

2017-01-01

In wireless powered sensor networks (WPSN), it is essential to research uplink transmit power control in order to achieve throughput performance balancing and energy scheduling. Each sensor should have an optimal transmit power level for revenue maximization. In this paper, we discuss a dynamic game-based algorithm for optimal power control in WPSN. The main idea is to use the non-cooperative differential game to control the uplink transmit power of wireless sensors in WPSN, to extend their working hours and to meet QoS (Quality of Services) requirements. Subsequently, the Nash equilibrium solutions are obtained through Bellman dynamic programming. At the same time, an uplink power control algorithm is proposed in a distributed manner. Through numerical simulations, we demonstrate that our algorithm can obtain optimal power control and reach convergence for an infinite horizon. PMID:28282945

Behavioral and Network Origins of Wealth Inequality: Insights from a Virtual World

PubMed Central

Fuchs, Benedikt; Thurner, Stefan

2014-01-01

Almost universally, wealth is not distributed uniformly within societies or economies. Even though wealth data have been collected in various forms for centuries, the origins for the observed wealth-disparity and social inequality are not yet fully understood. Especially the impact and connections of human behavior on wealth could so far not be inferred from data. Here we study wealth data from the virtual economy of the massive multiplayer online game (MMOG) Pardus. This data not only contains every player's wealth at every point in time, but also all actions over a timespan of almost a decade. We find that wealth distributions in the virtual world are very similar to those in Western countries. In particular we find an approximate exponential distribution for low wealth levels and a power-law tail for high levels. The Gini index is found to be , which is close to the indices of many Western countries. We find that wealth-increase rates depend on the time when players entered the game. Players that entered the game early on tend to have remarkably higher wealth-increase rates than those who joined later. Studying the players' positions within their social networks, we find that the local position in the trade network is most relevant for wealth. Wealthy people have high in- and out-degrees in the trade network, relatively low nearest-neighbor degrees, and low clustering coefficients. Wealthy players have many mutual friendships and are socially well respected by others, but spend more time on business than on socializing. Wealthy players have few personal enemies, but show animosity towards players that behave as public enemies. We find that players that are not organized within social groups are significantly poorer on average. We observe that “political” status and wealth go hand in hand. PMID:25153072

Behavioral and network origins of wealth inequality: insights from a virtual world.

PubMed

Fuchs, Benedikt; Thurner, Stefan

2014-01-01

Almost universally, wealth is not distributed uniformly within societies or economies. Even though wealth data have been collected in various forms for centuries, the origins for the observed wealth-disparity and social inequality are not yet fully understood. Especially the impact and connections of human behavior on wealth could so far not be inferred from data. Here we study wealth data from the virtual economy of the massive multiplayer online game (MMOG) Pardus. This data not only contains every player's wealth at every point in time, but also all actions over a timespan of almost a decade. We find that wealth distributions in the virtual world are very similar to those in Western countries. In particular we find an approximate exponential distribution for low wealth levels and a power-law tail for high levels. The Gini index is found to be g = 0.65, which is close to the indices of many Western countries. We find that wealth-increase rates depend on the time when players entered the game. Players that entered the game early on tend to have remarkably higher wealth-increase rates than those who joined later. Studying the players' positions within their social networks, we find that the local position in the trade network is most relevant for wealth. Wealthy people have high in- and out-degrees in the trade network, relatively low nearest-neighbor degrees, and low clustering coefficients. Wealthy players have many mutual friendships and are socially well respected by others, but spend more time on business than on socializing. Wealthy players have few personal enemies, but show animosity towards players that behave as public enemies. We find that players that are not organized within social groups are significantly poorer on average. We observe that "political" status and wealth go hand in hand.

Information spread in networks: Games, optimal control, and stabilization

NASA Astrophysics Data System (ADS)

Khanafer, Ali

This thesis focuses on designing efficient mechanisms for controlling information spread in networks. We consider two models for information spread. The first one is the well-known distributed averaging dynamics. The second model is a nonlinear one that describes virus spread in computer and biological networks. We seek to design optimal, robust, and stabilizing controllers under practical constraints. For distributed averaging networks, we study the interaction between a network designer and an adversary. We consider two types of attacks on the network. In Attack-I, the adversary strategically disconnects a set of links to prevent the nodes from reaching consensus. Meanwhile, the network designer assists the nodes in reaching consensus by changing the weights of a limited number of links in the network. We formulate two problems to describe this competition where the order in which the players act is reversed in the two problems. Although the canonical equations provided by the Pontryagin's Maximum Principle (MP) seem to be intractable, we provide an alternative characterization for the optimal strategies that makes connection to potential theory. Further, we provide a sufficient condition for the existence of a saddle-point equilibrium (SPE) for the underlying zero-sum game. In Attack-II, the designer and the adversary are both capable of altering the measurements of all nodes in the network by injecting global signals. We impose two constraints on both players: a power constraint and an energy constraint. We assume that the available energy to each player is not sufficient to operate at maximum power throughout the horizon of the game. We show the existence of an SPE and derive the optimal strategies in closed form for this attack scenario. As an alternative to the "network designer vs. adversary" framework, we investigate the possibility of stabilizing unknown network diffusion processes using a distributed mechanism, where the uncertainty is due to an attack on the network. To this end, we propose a distributed version of the classical logic-based supervisory control scheme. Given a network of agents whose dynamics contain unknown parameters, the distributed supervisory control scheme is used to assist the agents to converge to a certain set-point without requiring them to have explicit knowledge of that set-point. Unlike the classical supervisory control scheme where a centralized supervisor makes switching decisions among the candidate controllers, in our scheme, each agent is equipped with a local supervisor that switches among the available controllers. The switching decisions made at a certain agent depend only on the information from its neighboring agents. We provide sufficient conditions for stabilization and apply our framework to the distributed averaging problem in the presence of large modeling uncertainty. For infected networks, we study the stability properties of a susceptible-infected-susceptible (SIS) diffusion model, so-called the n-intertwined Markov model, over arbitrary network topologies. Similar to the majority of infection spread dynamics, this model exhibits a threshold phenomenon. When the curing rates in the network are high, the all-healthy state is the unique equilibrium over the network. Otherwise, an endemic equilibrium state emerges, where some infection remains within the network. Using notions from positive systems theory, we provide conditions for the global asymptotic stability of the equilibrium points in both cases over strongly and weakly connected directed networks based on the value of the basic reproduction number, a fundamental quantity in the study of epidemics. Furthermore, we demonstrate that the n-intertwined Markov model can be viewed as a best-response dynamical system of a concave game among the nodes. This characterization allows us to cast new infection spread dynamics; additionally, we provide a sufficient condition, for the global convergence to the all-healthy state, that can be checked in a distributed fashion. Moreover, we investigate the problem of stabilizing the network when the curing rates of a limited number of nodes can be controlled. In particular, we characterize the number of controllers required for a class of undirected graphs. We also design optimal controllers capable of minimizing the total infection in the network at minimum cost. Finally, we outline a set of open problems in the area of information spread control.

Distributed Multi-Cell Resource Allocation with Price Based ICI Coordination in Downlink OFDMA Networks

NASA Astrophysics Data System (ADS)

Lv, Gangming; Zhu, Shihua; Hui, Hui

Multi-cell resource allocation under minimum rate request for each user in OFDMA networks is addressed in this paper. Based on Lagrange dual decomposition theory, the joint multi-cell resource allocation problem is decomposed and modeled as a limited-cooperative game, and a distributed multi-cell resource allocation algorithm is thus proposed. Analysis and simulation results show that, compared with non-cooperative iterative water-filling algorithm, the proposed algorithm can remarkably reduce the ICI level and improve overall system performances.

Marginal Contribution-Based Distributed Subchannel Allocation in Small Cell Networks.

PubMed

Shah, Shashi; Kittipiyakul, Somsak; Lim, Yuto; Tan, Yasuo

2018-05-10

The paper presents a game theoretic solution for distributed subchannel allocation problem in small cell networks (SCNs) analyzed under the physical interference model. The objective is to find a distributed solution that maximizes the welfare of the SCNs, defined as the total system capacity. Although the problem can be addressed through best-response (BR) dynamics, the existence of a steady-state solution, i.e., a pure strategy Nash equilibrium (NE), cannot be guaranteed. Potential games (PGs) ensure convergence to a pure strategy NE when players rationally play according to some specified learning rules. However, such a performance guarantee comes at the expense of complete knowledge of the SCNs. To overcome such requirements, properties of PGs are exploited for scalable implementations, where we utilize the concept of marginal contribution (MC) as a tool to design learning rules of players’ utility and propose the marginal contribution-based best-response (MCBR) algorithm of low computational complexity for the distributed subchannel allocation problem. Finally, we validate and evaluate the proposed scheme through simulations for various performance metrics.

Evolutionary dynamics of the traveler's dilemma and minimum-effort coordination games on complex networks.

PubMed

Iyer, Swami; Killingback, Timothy

2014-10-01

The traveler's dilemma game and the minimum-effort coordination game are social dilemmas that have received significant attention resulting from the fact that the predictions of classical game theory are inconsistent with the results found when the games are studied experimentally. Moreover, both the traveler's dilemma and the minimum-effort coordination games have potentially important applications in evolutionary biology. Interestingly, standard deterministic evolutionary game theory, as represented by the replicator dynamics in a well-mixed population, is also inadequate to account for the behavior observed in these games. Here we study the evolutionary dynamics of both these games in populations with interaction patterns described by a variety of complex network topologies. We investigate the evolutionary dynamics of these games through agent-based simulations on both model and empirical networks. In particular, we study the effects of network clustering and assortativity on the evolutionary dynamics of both games. In general, we show that the evolutionary behavior of the traveler's dilemma and minimum-effort coordination games on complex networks is in good agreement with that observed experimentally. Thus, formulating the traveler's dilemma and the minimum-effort coordination games on complex networks neatly resolves the paradoxical aspects of these games.

Evolutionary dynamics of the traveler's dilemma and minimum-effort coordination games on complex networks

NASA Astrophysics Data System (ADS)

Iyer, Swami; Killingback, Timothy

2014-10-01

The traveler's dilemma game and the minimum-effort coordination game are social dilemmas that have received significant attention resulting from the fact that the predictions of classical game theory are inconsistent with the results found when the games are studied experimentally. Moreover, both the traveler's dilemma and the minimum-effort coordination games have potentially important applications in evolutionary biology. Interestingly, standard deterministic evolutionary game theory, as represented by the replicator dynamics in a well-mixed population, is also inadequate to account for the behavior observed in these games. Here we study the evolutionary dynamics of both these games in populations with interaction patterns described by a variety of complex network topologies. We investigate the evolutionary dynamics of these games through agent-based simulations on both model and empirical networks. In particular, we study the effects of network clustering and assortativity on the evolutionary dynamics of both games. In general, we show that the evolutionary behavior of the traveler's dilemma and minimum-effort coordination games on complex networks is in good agreement with that observed experimentally. Thus, formulating the traveler's dilemma and the minimum-effort coordination games on complex networks neatly resolves the paradoxical aspects of these games.

Evolution of imitation networks in Minority Game model

NASA Astrophysics Data System (ADS)

Lavička, H.; Slanina, F.

2007-03-01

The Minority Game is adapted to study the “imitation dilemma”, i.e. the tradeoff between local benefit and global harm coming from imitation. The agents are placed on a substrate network and are allowed to imitate more successful neighbours. Imitation domains, which are oriented trees, are formed. We investigate size distribution of the domains and in-degree distribution within the trees. We use four types of substrate: one-dimensional chain; Erdös-Rényi graph; Barabási-Albert scale-free graph; Barabási-Albert 'model A' graph. The behaviour of some features of the imitation network strongly depend on the information cost epsilon, which is the percentage of gain the imitators must pay to the imitated. Generally, the system tends to form a few domains of equal size. However, positive epsilon makes the system stay in a long-lasting metastable state with complex structure. The in-degree distribution is found to follow a power law in two cases of those studied: for Erdös-Rényi substrate for any epsilon and for Barabási-Albert scale-free substrate for large enough epsilon. A brief comparison with empirical data is provided.

Games network and application to PAs system.

PubMed

Chettaoui, C; Delaplace, F; Manceny, M; Malo, M

2007-02-01

In this article, we present a game theory based framework, named games network, for modeling biological interactions. After introducing the theory, we more precisely describe the methodology to model biological interactions. Then we apply it to the plasminogen activator system (PAs) which is a signal transduction pathway involved in cancer cell migration. The games network theory extends game theory by including the locality of interactions. Each game in a games network represents local interactions between biological agents. The PAs system is implicated in cytoskeleton modifications via regulation of actin and microtubules, which in turn favors cell migration. The games network model has enabled us a better understanding of the regulation involved in the PAs system.

Graph Design via Convex Optimization: Online and Distributed Perspectives

NASA Astrophysics Data System (ADS)

Meng, De

Network and graph have long been natural abstraction of relations in a variety of applications, e.g. transportation, power system, social network, communication, electrical circuit, etc. As a large number of computation and optimization problems are naturally defined on graphs, graph structures not only enable important properties of these problems, but also leads to highly efficient distributed and online algorithms. For example, graph separability enables the parallelism for computation and operation as well as limits the size of local problems. More interestingly, graphs can be defined and constructed in order to take best advantage of those problem properties. This dissertation focuses on graph structure and design in newly proposed optimization problems, which establish a bridge between graph properties and optimization problem properties. We first study a new optimization problem called Geodesic Distance Maximization Problem (GDMP). Given a graph with fixed edge weights, finding the shortest path, also known as the geodesic, between two nodes is a well-studied network flow problem. We introduce the Geodesic Distance Maximization Problem (GDMP): the problem of finding the edge weights that maximize the length of the geodesic subject to convex constraints on the weights. We show that GDMP is a convex optimization problem for a wide class of flow costs, and provide a physical interpretation using the dual. We present applications of the GDMP in various fields, including optical lens design, network interdiction, and resource allocation in the control of forest fires. We develop an Alternating Direction Method of Multipliers (ADMM) by exploiting specific problem structures to solve large-scale GDMP, and demonstrate its effectiveness in numerical examples. We then turn our attention to distributed optimization on graph with only local communication. Distributed optimization arises in a variety of applications, e.g. distributed tracking and localization, estimation problems in sensor networks, multi-agent coordination. Distributed optimization aims to optimize a global objective function formed by summation of coupled local functions over a graph via only local communication and computation. We developed a weighted proximal ADMM for distributed optimization using graph structure. This fully distributed, single-loop algorithm allows simultaneous updates and can be viewed as a generalization of existing algorithms. More importantly, we achieve faster convergence by jointly designing graph weights and algorithm parameters. Finally, we propose a new problem on networks called Online Network Formation Problem: starting with a base graph and a set of candidate edges, at each round of the game, player one first chooses a candidate edge and reveals it to player two, then player two decides whether to accept it; player two can only accept limited number of edges and make online decisions with the goal to achieve the best properties of the synthesized network. The network properties considered include the number of spanning trees, algebraic connectivity and total effective resistance. These network formation games arise in a variety of cooperative multiagent systems. We propose a primal-dual algorithm framework for the general online network formation game, and analyze the algorithm performance by the competitive ratio and regret.

Action Video Game Experience Related to Altered Large-Scale White Matter Networks.

PubMed

Gong, Diankun; Ma, Weiyi; Gong, Jinnan; He, Hui; Dong, Li; Zhang, Dan; Li, Jianfu; Luo, Cheng; Yao, Dezhong

2017-01-01

With action video games (AVGs) becoming increasingly popular worldwide, the cognitive benefits of AVG experience have attracted continuous research attention over the past two decades. Research has repeatedly shown that AVG experience can causally enhance cognitive ability and is related to neural plasticity in gray matter and functional networks in the brain. However, the relation between AVG experience and the plasticity of white matter (WM) network still remains unclear. WM network modulates the distribution of action potentials, coordinating the communication between brain regions and acting as the framework of neural networks. And various types of cognitive deficits are usually accompanied by impairments of WM networks. Thus, understanding this relation is essential in assessing the influence of AVG experience on neural plasticity and using AVG experience as an interventional tool for impairments of WM networks. Using graph theory, this study analyzed WM networks in AVG experts and amateurs. Results showed that AVG experience is related to altered WM networks in prefrontal networks, limbic system, and sensorimotor networks, which are related to cognitive control and sensorimotor functions. These results shed new light on the influence of AVG experience on the plasticity of WM networks and suggested the clinical applicability of AVG experience.

War-Gaming Network-Centric Warfare

DTIC Science & Technology

2001-01-01

games as well. 6 2 N A V A L W A R C O L L E G E R E V I E W War games are also classified...traditional gaming . All war games , whether they involve fighting sail R U B E L 6 3 Until a tactical network of units, each of them exercising a great degree... gaming and simulation. R U B E L 6 5 The principal requirements for achieving network-centric warfare are a network and shared awareness. By a

Evaluating the benefits of collaboration in simulation games: the case of health care.

PubMed

Leung, Ricky

2014-01-28

Organizations have used simulation games for health promotion and communication. To evaluate how simulation games can foster collaboration among stakeholders, this paper develops two social network measures. The paper aims to initiate two specific measures that facilitate organizations and researchers to evaluate the effectiveness of Web-based simulation games in fostering collaboration. The two measures are: (1) network density and (2) network diversity. They measure the level of connectedness and communication evenness within social networks. To illustrate how these measures may be used, a hypothetical game about health policy is outlined. Web-based games can serve as an effective platform to engage stakeholders because interaction among them is quite convenient. Yet, systematic evaluation and planning are necessary to realize the benefits of these games. The paper suggests directions for testing how the social network dimension of Web-based games can augment individual-level benefits that stakeholders can obtain from playing simulation games. While this paper focuses on measuring the structural properties of social networks in Web-based games, further research should focus more attention on the appropriateness of game contents. In addition, empirical research should cover different geographical areas, such as East Asian countries where video games are very popular.

Improved Lower Bounds on the Price of Stability of Undirected Network Design Games

NASA Astrophysics Data System (ADS)

Bilò, Vittorio; Caragiannis, Ioannis; Fanelli, Angelo; Monaco, Gianpiero

Bounding the price of stability of undirected network design games with fair cost allocation is a challenging open problem in the Algorithmic Game Theory research agenda. Even though the generalization of such games in directed networks is well understood in terms of the price of stability (it is exactly H n , the n-th harmonic number, for games with n players), far less is known for network design games in undirected networks. The upper bound carries over to this case as well while the best known lower bound is 42/23 ≈ 1.826. For more restricted but interesting variants of such games such as broadcast and multicast games, sublogarithmic upper bounds are known while the best known lower bound is 12/7 ≈ 1.714. In the current paper, we improve the lower bounds as follows. We break the psychological barrier of 2 by showing that the price of stability of undirected network design games is at least 348/155 ≈ 2.245. Our proof uses a recursive construction of a network design game with a simple gadget as the main building block. For broadcast and multicast games, we present new lower bounds of 20/11 ≈ 1.818 and 1.862, respectively.

Serving by local consensus in the public service location game.

PubMed

Sun, Yi-Fan; Zhou, Hai-Jun

2016-09-02

We discuss the issue of distributed and cooperative decision-making in a network game of public service location. Each node of the network can decide to host a certain public service incurring in a construction cost and serving all the neighboring nodes and itself. A pure consumer node has to pay a tax, and the collected tax is evenly distributed to all the hosting nodes to remedy their construction costs. If all nodes make individual best-response decisions, the system gets trapped in an inefficient situation of high tax level. Here we introduce a decentralized local-consensus selection mechanism which requires nodes to recommend their neighbors of highest local impact as candidate servers, and a node may become a server only if all its non-server neighbors give their assent. We demonstrate that although this mechanism involves only information exchange among neighboring nodes, it leads to socially efficient solutions with tax level approaching the lowest possible value. Our results may help in understanding and improving collective problem-solving in various networked social and robotic systems.

Serving by local consensus in the public service location game

PubMed Central

Sun, Yi-Fan; Zhou, Hai-Jun

2016-01-01

We discuss the issue of distributed and cooperative decision-making in a network game of public service location. Each node of the network can decide to host a certain public service incurring in a construction cost and serving all the neighboring nodes and itself. A pure consumer node has to pay a tax, and the collected tax is evenly distributed to all the hosting nodes to remedy their construction costs. If all nodes make individual best-response decisions, the system gets trapped in an inefficient situation of high tax level. Here we introduce a decentralized local-consensus selection mechanism which requires nodes to recommend their neighbors of highest local impact as candidate servers, and a node may become a server only if all its non-server neighbors give their assent. We demonstrate that although this mechanism involves only information exchange among neighboring nodes, it leads to socially efficient solutions with tax level approaching the lowest possible value. Our results may help in understanding and improving collective problem-solving in various networked social and robotic systems. PMID:27586793

Serving by local consensus in the public service location game

NASA Astrophysics Data System (ADS)

Sun, Yi-Fan; Zhou, Hai-Jun

2016-09-01

We discuss the issue of distributed and cooperative decision-making in a network game of public service location. Each node of the network can decide to host a certain public service incurring in a construction cost and serving all the neighboring nodes and itself. A pure consumer node has to pay a tax, and the collected tax is evenly distributed to all the hosting nodes to remedy their construction costs. If all nodes make individual best-response decisions, the system gets trapped in an inefficient situation of high tax level. Here we introduce a decentralized local-consensus selection mechanism which requires nodes to recommend their neighbors of highest local impact as candidate servers, and a node may become a server only if all its non-server neighbors give their assent. We demonstrate that although this mechanism involves only information exchange among neighboring nodes, it leads to socially efficient solutions with tax level approaching the lowest possible value. Our results may help in understanding and improving collective problem-solving in various networked social and robotic systems.

Exact solutions for network rewiring models

NASA Astrophysics Data System (ADS)

Evans, T. S.

2007-03-01

Evolving networks with a constant number of edges may be modelled using a rewiring process. These models are used to describe many real-world processes including the evolution of cultural artifacts such as family names, the evolution of gene variations, and the popularity of strategies in simple econophysics models such as the minority game. The model is closely related to Urn models used for glasses, quantum gravity and wealth distributions. The full mean field equation for the degree distribution is found and its exact solution and generating solution are given.

Mean-Field Games for Marriage

PubMed Central

Bauso, Dario; Dia, Ben Mansour; Djehiche, Boualem; Tembine, Hamidou; Tempone, Raul

2014-01-01

This article examines mean-field games for marriage. The results support the argument that optimizing the long-term well-being through effort and social feeling state distribution (mean-field) will help to stabilize marriage. However, if the cost of effort is very high, the couple fluctuates in a bad feeling state or the marriage breaks down. We then examine the influence of society on a couple using mean-field sentimental games. We show that, in mean-field equilibrium, the optimal effort is always higher than the one-shot optimal effort. We illustrate numerically the influence of the couple’s network on their feeling states and their well-being. PMID:24804835

Mean-field games for marriage.

PubMed

Bauso, Dario; Dia, Ben Mansour; Djehiche, Boualem; Tembine, Hamidou; Tempone, Raul

2014-01-01

This article examines mean-field games for marriage. The results support the argument that optimizing the long-term well-being through effort and social feeling state distribution (mean-field) will help to stabilize marriage. However, if the cost of effort is very high, the couple fluctuates in a bad feeling state or the marriage breaks down. We then examine the influence of society on a couple using mean-field sentimental games. We show that, in mean-field equilibrium, the optimal effort is always higher than the one-shot optimal effort. We illustrate numerically the influence of the couple's network on their feeling states and their well-being.

Dynamics, morphogenesis and convergence of evolutionary quantum Prisoner's Dilemma games on networks

PubMed Central

Yong, Xi

2016-01-01

The authors proposed a quantum Prisoner's Dilemma (PD) game as a natural extension of the classic PD game to resolve the dilemma. Here, we establish a new Nash equilibrium principle of the game, propose the notion of convergence and discover the convergence and phase-transition phenomena of the evolutionary games on networks. We investigate the many-body extension of the game or evolutionary games in networks. For homogeneous networks, we show that entanglement guarantees a quick convergence of super cooperation, that there is a phase transition from the convergence of defection to the convergence of super cooperation, and that the threshold for the phase transitions is principally determined by the Nash equilibrium principle of the game, with an accompanying perturbation by the variations of structures of networks. For heterogeneous networks, we show that the equilibrium frequencies of super-cooperators are divergent, that entanglement guarantees emergence of super-cooperation and that there is a phase transition of the emergence with the threshold determined by the Nash equilibrium principle, accompanied by a perturbation by the variations of structures of networks. Our results explore systematically, for the first time, the dynamics, morphogenesis and convergence of evolutionary games in interacting and competing systems. PMID:27118882

An improved game-theoretic approach to uncover overlapping communities

NASA Astrophysics Data System (ADS)

Sun, Hong-Liang; Ch'Ng, Eugene; Yong, Xi; Garibaldi, Jonathan M.; See, Simon; Chen, Duan-Bing

How can we uncover overlapping communities from complex networks to understand the inherent structures and functions? Chen et al. firstly proposed a community game (Game) to study this problem, and the overlapping communities have been discovered when the game is convergent. It is based on the assumption that each vertex of the underlying network is a rational game player to maximize its utility. In this paper, we investigate how similar vertices affect the formation of community game. The Adamic-Adar Index (AA Index) has been employed to define the new utility function. This novel method has been evaluated on both synthetic and real-world networks. Experimental study shows that it has significant improvement of accuracy (from 4.8% to 37.6%) compared with the Game on 10 real networks. It is more efficient on Facebook networks (FN) and Amazon co-purchasing networks than on other networks. This result implicates that “friend circles of friends” of Facebook are valuable to understand the overlapping community division.

Distinguishing humans from computers in the game of go: A complex network approach

NASA Astrophysics Data System (ADS)

Coquidé, C.; Georgeot, B.; Giraud, O.

2017-08-01

We compare complex networks built from the game of go and obtained from databases of human-played games with those obtained from computer-played games. Our investigations show that statistical features of the human-based networks and the computer-based networks differ, and that these differences can be statistically significant on a relatively small number of games using specific estimators. We show that the deterministic or stochastic nature of the computer algorithm playing the game can also be distinguished from these quantities. This can be seen as a tool to implement a Turing-like test for go simulators.

Security-Oriented and Load-Balancing Wireless Data Routing Game in the Integration of Advanced Metering Infrastructure Network in Smart Grid

DOE Office of Scientific and Technical Information (OSTI.GOV)

He, Fulin; Cao, Yang; Zhang, Jun Jason

Ensuring flexible and reliable data routing is indispensable for the integration of Advanced Metering Infrastructure (AMI) networks, we propose a secure-oriented and load-balancing wireless data routing scheme. A novel utility function is designed based on security routing scheme. Then, we model the interactive security-oriented routing strategy among meter data concentrators or smart grid meters as a mixed-strategy network formation game. Finally, such problem results in a stable probabilistic routing scheme with proposed distributed learning algorithm. One contributions is that we studied that different types of applications affect the routing selection strategy and the strategy tendency. Another contributions is that themore » chosen strategy of our mixed routing can adaptively to converge to a new mixed strategy Nash equilibrium (MSNE) during the learning process in the smart grid.« less

ASIST 2001. Information in a Networked World: Harnessing the Flow. Part III: Poster Presentations.

ERIC Educational Resources Information Center

Proceedings of the ASIST Annual Meeting, 2001

2001-01-01

Topics of Poster Presentations include: electronic preprints; intranets; poster session abstracts; metadata; information retrieval; watermark images; video games; distributed information retrieval; subject domain knowledge; data mining; information theory; course development; historians' use of pictorial images; information retrieval software;…

Distributed Observer Network

NASA Technical Reports Server (NTRS)

2008-01-01

NASA s advanced visual simulations are essential for analyses associated with life cycle planning, design, training, testing, operations, and evaluation. Kennedy Space Center, in particular, uses simulations for ground services and space exploration planning in an effort to reduce risk and costs while improving safety and performance. However, it has been difficult to circulate and share the results of simulation tools among the field centers, and distance and travel expenses have made timely collaboration even harder. In response, NASA joined with Valador Inc. to develop the Distributed Observer Network (DON), a collaborative environment that leverages game technology to bring 3-D simulations to conventional desktop and laptop computers. DON enables teams of engineers working on design and operations to view and collaborate on 3-D representations of data generated by authoritative tools. DON takes models and telemetry from these sources and, using commercial game engine technology, displays the simulation results in a 3-D visual environment. Multiple widely dispersed users, working individually or in groups, can view and analyze simulation results on desktop and laptop computers in real time.

A game theory approach to target tracking in sensor networks.

PubMed

Gu, Dongbing

2011-02-01

In this paper, we investigate a moving-target tracking problem with sensor networks. Each sensor node has a sensor to observe the target and a processor to estimate the target position. It also has wireless communication capability but with limited range and can only communicate with neighbors. The moving target is assumed to be an intelligent agent, which is "smart" enough to escape from the detection by maximizing the estimation error. This adversary behavior makes the target tracking problem more difficult. We formulate this target estimation problem as a zero-sum game in this paper and use a minimax filter to estimate the target position. The minimax filter is a robust filter that minimizes the estimation error by considering the worst case noise. Furthermore, we develop a distributed version of the minimax filter for multiple sensor nodes. The distributed computation is implemented via modeling the information received from neighbors as measurements in the minimax filter. The simulation results show that the target tracking algorithm proposed in this paper provides a satisfactory result.

Achieving Congestion Mitigation Using Distributed Power Control for Spectrum Sensor Nodes in Sensor Network-Aided Cognitive Radio Ad Hoc Networks

PubMed Central

Zhuo, Fan; Duan, Hucai

2017-01-01

The data sequence of spectrum sensing results injected from dedicated spectrum sensor nodes (SSNs) and the data traffic from upstream secondary users (SUs) lead to unpredictable data loads in a sensor network-aided cognitive radio ad hoc network (SN-CRN). As a result, network congestion may occur at a SU acting as fusion center when the offered data load exceeds its available capacity, which degrades network performance. In this paper, we present an effective approach to mitigate congestion of bottlenecked SUs via a proposed distributed power control framework for SSNs over a rectangular grid based SN-CRN, aiming to balance resource load and avoid excessive congestion. To achieve this goal, a distributed power control framework for SSNs from interior tier (IT) and middle tier (MT) is proposed to achieve the tradeoff between channel capacity and energy consumption. In particular, we firstly devise two pricing factors by considering stability of local spectrum sensing and spectrum sensing quality for SSNs. By the aid of pricing factors, the utility function of this power control problem is formulated by jointly taking into account the revenue of power reduction and the cost of energy consumption for IT or MT SSN. By bearing in mind the utility function maximization and linear differential equation constraint of energy consumption, we further formulate the power control problem as a differential game model under a cooperation or noncooperation scenario, and rigorously obtain the optimal solutions to this game model by employing dynamic programming. Then the congestion mitigation for bottlenecked SUs is derived by alleviating the buffer load over their internal buffers. Simulation results are presented to show the effectiveness of the proposed approach under the rectangular grid based SN-CRN scenario. PMID:28914803

Application of Game Theory Approaches in Routing Protocols for Wireless Networks

NASA Astrophysics Data System (ADS)

Javidi, Mohammad M.; Aliahmadipour, Laya

2011-09-01

An important and essential issue for wireless networks is routing protocol design that is a major technical challenge due to the function of the network. Game theory is a powerful mathematical tool that analyzes the strategic interactions among multiple decision makers and the results of researches show that applied game theory in routing protocol lead to improvement the network performance through reduce overhead and motivates selfish nodes to collaborate in the network. This paper presents a review and comparison for typical representatives of routing protocols designed that applied game theory approaches for various wireless networks such as ad hoc networks, mobile ad hoc networks and sensor networks that all of them lead to improve the network performance.

Emergence of Super Cooperation of Prisoner’s Dilemma Games on Scale-Free Networks

PubMed Central

Li, Angsheng; Yong, Xi

2015-01-01

Recently, the authors proposed a quantum prisoner’s dilemma game based on the spatial game of Nowak and May, and showed that the game can be played classically. By using this idea, we proposed three generalized prisoner’s dilemma (GPD, for short) games based on the weak Prisoner’s dilemma game, the full prisoner’s dilemma game and the normalized Prisoner’s dilemma game, written by GPDW, GPDF and GPDN respectively. Our games consist of two players, each of which has three strategies: cooperator (C), defector (D) and super cooperator (denoted by Q), and have a parameter γ to measure the entangled relationship between the two players. We found that our generalised prisoner’s dilemma games have new Nash equilibrium principles, that entanglement is the principle of emergence and convergence (i.e., guaranteed emergence) of super cooperation in evolutions of our generalised prisoner’s dilemma games on scale-free networks, that entanglement provides a threshold for a phase transition of super cooperation in evolutions of our generalised prisoner’s dilemma games on scale-free networks, that the role of heterogeneity of the scale-free networks in cooperations and super cooperations is very limited, and that well-defined structures of scale-free networks allow coexistence of cooperators and super cooperators in the evolutions of the weak version of our generalised prisoner’s dilemma games. PMID:25643279

Evolutionary Games in Multi-Agent Systems of Weighted Social Networks

NASA Astrophysics Data System (ADS)

Du, Wen-Bo; Cao, Xian-Bin; Zheng, Hao-Ran; Zhou, Hong; Hu, Mao-Bin

Much empirical evidence has shown realistic networks are weighted. Compared with those on unweighted networks, the dynamics on weighted network often exhibit distinctly different phenomena. In this paper, we investigate the evolutionary game dynamics (prisoner's dilemma game and snowdrift game) on a weighted social network consisted of rational agents and focus on the evolution of cooperation in the system. Simulation results show that the cooperation level is strongly affected by the weighted nature of the network. Moreover, the variation of time series has also been investigated. Our work may be helpful in understanding the cooperative behavior in the social systems.

Research on Information Sharing Mechanism of Network Organization Based on Evolutionary Game

NASA Astrophysics Data System (ADS)

Wang, Lin; Liu, Gaozhi

2018-02-01

This article first elaborates the concept and effect of network organization, and the ability to share information is analyzed, secondly introduces the evolutionary game theory, network organization for information sharing all kinds of limitations, establishes the evolutionary game model, analyzes the dynamic evolution of network organization of information sharing, through reasoning and evolution. The network information sharing by the initial state and two sides of the game payoff matrix of excess profits and information is the information sharing of cost and risk sharing are the influence of network organization node information sharing decision.

Quantum Prisoner’s Dilemma game on hypergraph networks

NASA Astrophysics Data System (ADS)

Pawela, Łukasz; Sładkowski, Jan

2013-02-01

We study the possible advantages of adopting quantum strategies in multi-player evolutionary games. We base our study on the three-player Prisoner’s Dilemma (PD) game. In order to model the simultaneous interaction between three agents we use hypergraphs and hypergraph networks. In particular, we study two types of networks: a random network and a SF-like network. The obtained results show that in the case of a three-player game on a hypergraph network, quantum strategies are not necessarily stochastically stable strategies. In some cases, the defection strategy can be as good as a quantum one.

Relational Diversity Promotes Cooperation in Prisoner’s Dilemma Games

PubMed Central

Xu, Bo; Wang, Jianwei; Deng, Ruipu; Li, Miao

2014-01-01

Relational diversity can be characterized by heterogeneous distributions of tie strengths in social networks and this diversity is present not only among humans, but throughout the animal world. We account for this observation by analyzing two network datasets from Facebook. We measure the strength of a tie by calculating the extent of overlap of friends between the two individuals. Based on the previous findings in human experiments, we argue that it is very unlikely that players will allocate their investments equally to their neighbors. There is a tendency that players prefer to donate more to their intimate friends. We find that if players preferentially allocate their investments to their good friends, cooperation will be promoted in PDG. We proved that the facilitation of the cooperative strategy relies mostly on the cooperative allies between best friends, resulting in the formation of cooperative clusters which are able to prevail against the defectors even when there is a large cost to cooperate. Moreover, we discover that the effect of relational diversity cannot be analyzed by adopting classical complex networks models, because neither of the artificial networks is able to produce networks with diverse distributions of tie strengths. It is of vital importance to introduce real social networks to study the influence of diverse relations especially when it comes to humans. This research proposes a brand new perspective to understand the influence of social relations on the emergence of cooperation in evolutionary prisoner’s dilemma games. PMID:25474354

Relational diversity promotes cooperation in prisoner's dilemma games.

PubMed

Xu, Bo; Wang, Jianwei; Deng, Ruipu; Li, Miao

2014-01-01

Relational diversity can be characterized by heterogeneous distributions of tie strengths in social networks and this diversity is present not only among humans, but throughout the animal world. We account for this observation by analyzing two network datasets from Facebook. We measure the strength of a tie by calculating the extent of overlap of friends between the two individuals. Based on the previous findings in human experiments, we argue that it is very unlikely that players will allocate their investments equally to their neighbors. There is a tendency that players prefer to donate more to their intimate friends. We find that if players preferentially allocate their investments to their good friends, cooperation will be promoted in PDG. We proved that the facilitation of the cooperative strategy relies mostly on the cooperative allies between best friends, resulting in the formation of cooperative clusters which are able to prevail against the defectors even when there is a large cost to cooperate. Moreover, we discover that the effect of relational diversity cannot be analyzed by adopting classical complex networks models, because neither of the artificial networks is able to produce networks with diverse distributions of tie strengths. It is of vital importance to introduce real social networks to study the influence of diverse relations especially when it comes to humans. This research proposes a brand new perspective to understand the influence of social relations on the emergence of cooperation in evolutionary prisoner's dilemma games.

Mapping Systemic Risk: Critical Degree and Failures Distribution in Financial Networks.

PubMed

Smerlak, Matteo; Stoll, Brady; Gupta, Agam; Magdanz, James S

2015-01-01

The financial crisis illustrated the need for a functional understanding of systemic risk in strongly interconnected financial structures. Dynamic processes on complex networks being intrinsically difficult to model analytically, most recent studies of this problem have relied on numerical simulations. Here we report analytical results in a network model of interbank lending based on directly relevant financial parameters, such as interest rates and leverage ratios. We obtain a closed-form formula for the "critical degree" (the number of creditors per bank below which an individual shock can propagate throughout the network), and relate failures distributions to network topologies, in particular scalefree ones. Our criterion for the onset of contagion turns out to be isomorphic to the condition for cooperation to evolve on graphs and social networks, as recently formulated in evolutionary game theory. This remarkable connection supports recent calls for a methodological rapprochement between finance and ecology.

Mapping Systemic Risk: Critical Degree and Failures Distribution in Financial Networks

PubMed Central

Smerlak, Matteo; Stoll, Brady; Gupta, Agam; Magdanz, James S.

2015-01-01

The financial crisis illustrated the need for a functional understanding of systemic risk in strongly interconnected financial structures. Dynamic processes on complex networks being intrinsically difficult to model analytically, most recent studies of this problem have relied on numerical simulations. Here we report analytical results in a network model of interbank lending based on directly relevant financial parameters, such as interest rates and leverage ratios. We obtain a closed-form formula for the “critical degree” (the number of creditors per bank below which an individual shock can propagate throughout the network), and relate failures distributions to network topologies, in particular scalefree ones. Our criterion for the onset of contagion turns out to be isomorphic to the condition for cooperation to evolve on graphs and social networks, as recently formulated in evolutionary game theory. This remarkable connection supports recent calls for a methodological rapprochement between finance and ecology. PMID:26207631

Identifying protein complexes in PPI network using non-cooperative sequential game.

PubMed

Maulik, Ujjwal; Basu, Srinka; Ray, Sumanta

2017-08-21

Identifying protein complexes from protein-protein interaction (PPI) network is an important and challenging task in computational biology as it helps in better understanding of cellular mechanisms in various organisms. In this paper we propose a noncooperative sequential game based model for protein complex detection from PPI network. The key hypothesis is that protein complex formation is driven by mechanism that eventually optimizes the number of interactions within the complex leading to dense subgraph. The hypothesis is drawn from the observed network property named small world. The proposed multi-player game model translates the hypothesis into the game strategies. The Nash equilibrium of the game corresponds to a network partition where each protein either belong to a complex or form a singleton cluster. We further propose an algorithm to find the Nash equilibrium of the sequential game. The exhaustive experiment on synthetic benchmark and real life yeast networks evaluates the structural as well as biological significance of the network partitions.

Use of behavioral biometrics in intrusion detection and online gaming

NASA Astrophysics Data System (ADS)

Yampolskiy, Roman V.; Govindaraju, Venu

2006-04-01

Behavior based intrusion detection is a frequently used approach for insuring network security. We expend behavior based intrusion detection approach to a new domain of game networks. Specifically, our research shows that a unique behavioral biometric can be generated based on the strategy used by an individual to play a game. We wrote software capable of automatically extracting behavioral profiles for each player in a game of Poker. Once a behavioral signature is generated for a player, it is continuously compared against player's current actions. Any significant deviations in behavior are reported to the game server administrator as potential security breaches. Our algorithm addresses a well-known problem of user verification and can be re-applied to the fields beyond game networks, such as operating systems and non-game networks security.

Efficiency analysis on platform over the top (OTT) to deploy content and applications (edutainment) in digital television on optical network link

NASA Astrophysics Data System (ADS)

Puche, William S.; Sierra, Javier E.; Moreno, Gustavo A.

2014-08-01

The convergence of new technologies in the digital world has made devices with internet connectivity such as televisions, smatphone, Tablet, Blu-ray, game consoles, among others, to increase more and more. Therefore the major research centers are in the task of improving the network performance to mitigate the bottle neck phenomenon regarding capacity and high transmission rates in information and data. The implementation of standard HbbTV (Hybrid Broadcast Broadband TV), and technological platforms OTT (Over the Top), capable of distributing video, audio, TV, and other Internet services via devices connected directly to the cloud. Therefore a model to improve the transmission capacity required by content distribution networks (CDN) for online TV, with high-capacity optical networks is proposed.

A consensus opinion model based on the evolutionary game

NASA Astrophysics Data System (ADS)

Yang, Han-Xin

2016-08-01

We propose a consensus opinion model based on the evolutionary game. In our model, both of the two connected agents receive a benefit if they have the same opinion, otherwise they both pay a cost. Agents update their opinions by comparing payoffs with neighbors. The opinion of an agent with higher payoff is more likely to be imitated. We apply this model in scale-free networks with tunable degree distribution. Interestingly, we find that there exists an optimal ratio of cost to benefit, leading to the shortest consensus time. Qualitative analysis is obtained by examining the evolution of the opinion clusters. Moreover, we find that the consensus time decreases as the average degree of the network increases, but increases with the noise introduced to permit irrational choices. The dependence of the consensus time on the network size is found to be a power-law form. For small or larger ratio of cost to benefit, the consensus time decreases as the degree exponent increases. However, for moderate ratio of cost to benefit, the consensus time increases with the degree exponent. Our results may provide new insights into opinion dynamics driven by the evolutionary game theory.

Mastering the game of Go with deep neural networks and tree search.

PubMed

Silver, David; Huang, Aja; Maddison, Chris J; Guez, Arthur; Sifre, Laurent; van den Driessche, George; Schrittwieser, Julian; Antonoglou, Ioannis; Panneershelvam, Veda; Lanctot, Marc; Dieleman, Sander; Grewe, Dominik; Nham, John; Kalchbrenner, Nal; Sutskever, Ilya; Lillicrap, Timothy; Leach, Madeleine; Kavukcuoglu, Koray; Graepel, Thore; Hassabis, Demis

2016-01-28

The game of Go has long been viewed as the most challenging of classic games for artificial intelligence owing to its enormous search space and the difficulty of evaluating board positions and moves. Here we introduce a new approach to computer Go that uses 'value networks' to evaluate board positions and 'policy networks' to select moves. These deep neural networks are trained by a novel combination of supervised learning from human expert games, and reinforcement learning from games of self-play. Without any lookahead search, the neural networks play Go at the level of state-of-the-art Monte Carlo tree search programs that simulate thousands of random games of self-play. We also introduce a new search algorithm that combines Monte Carlo simulation with value and policy networks. Using this search algorithm, our program AlphaGo achieved a 99.8% winning rate against other Go programs, and defeated the human European Go champion by 5 games to 0. This is the first time that a computer program has defeated a human professional player in the full-sized game of Go, a feat previously thought to be at least a decade away.

Coevolutionary, coexisting learning and teaching agents model for prisoner’s dilemma games enhancing cooperation with assortative heterogeneous networks

NASA Astrophysics Data System (ADS)

Tanimoto, Jun

2013-07-01

Unlike other natural network systems, assortativity can be observed in most human social networks, although it has been reported that a social dilemma situation represented by the prisoner’s dilemma favors dissortativity to enhance cooperation. We established a new coevolutionary model for both agents’ strategy and network topology, where teaching and learning agents coexist. Remarkably, this model enables agents’ enhancing cooperation more than a learners-only model on a time-frozen scale-free network and produces an underlying assortative network with a fair degree of power-law distribution. The model may imply how and why assortative networks are adaptive in human society.

Opinion formation in time-varying social networks: The case of the naming game

NASA Astrophysics Data System (ADS)

Maity, Suman Kalyan; Manoj, T. Venkat; Mukherjee, Animesh

2012-09-01

We study the dynamics of the naming game as an opinion formation model on time-varying social networks. This agent-based model captures the essential features of the agreement dynamics by means of a memory-based negotiation process. Our study focuses on the impact of time-varying properties of the social network of the agents on the naming game dynamics. In particular, we perform a computational exploration of this model using simulations on top of real networks. We investigate the outcomes of the dynamics on two different types of time-varying data: (1) the networks vary on a day-to-day basis and (2) the networks vary within very short intervals of time (20 sec). In the first case, we find that networks with strong community structure hinder the system from reaching global agreement; the evolution of the naming game in these networks maintains clusters of coexisting opinions indefinitely leading to metastability. In the second case, we investigate the evolution of the naming game in perfect synchronization with the time evolution of the underlying social network shedding new light on the traditional emergent properties of the game that differ largely from what has been reported in the existing literature.

Unfavorable Individuals in Social Gaming Networks.

PubMed

Zhang, Yichao; Chen, Guanrong; Guan, Jihong; Zhang, Zhongzhi; Zhou, Shuigeng

2015-12-09

In social gaming networks, the current research focus has been on the origin of widespread reciprocal behaviors when individuals play non-cooperative games. In this paper, we investigate the topological properties of unfavorable individuals in evolutionary games. The unfavorable individuals are defined as the individuals gaining the lowest average payoff in a round of game. Since the average payoff is normally considered as a measure of fitness, the unfavorable individuals are very likely to be eliminated or change their strategy updating rules from a Darwinian perspective. Considering that humans can hardly adopt a unified strategy to play with their neighbors, we propose a divide-and-conquer game model, where individuals can interact with their neighbors in the network with appropriate strategies. We test and compare a series of highly rational strategy updating rules. In the tested scenarios, our analytical and simulation results surprisingly reveal that the less-connected individuals in degree-heterogeneous networks are more likely to become the unfavorable individuals. Our finding suggests that the connectivity of individuals as a social capital fundamentally changes the gaming environment. Our model, therefore, provides a theoretical framework for further understanding the social gaming networks.

Unfavorable Individuals in Social Gaming Networks

NASA Astrophysics Data System (ADS)

Zhang, Yichao; Chen, Guanrong; Guan, Jihong; Zhang, Zhongzhi; Zhou, Shuigeng

2015-12-01

In social gaming networks, the current research focus has been on the origin of widespread reciprocal behaviors when individuals play non-cooperative games. In this paper, we investigate the topological properties of unfavorable individuals in evolutionary games. The unfavorable individuals are defined as the individuals gaining the lowest average payoff in a round of game. Since the average payoff is normally considered as a measure of fitness, the unfavorable individuals are very likely to be eliminated or change their strategy updating rules from a Darwinian perspective. Considering that humans can hardly adopt a unified strategy to play with their neighbors, we propose a divide-and-conquer game model, where individuals can interact with their neighbors in the network with appropriate strategies. We test and compare a series of highly rational strategy updating rules. In the tested scenarios, our analytical and simulation results surprisingly reveal that the less-connected individuals in degree-heterogeneous networks are more likely to become the unfavorable individuals. Our finding suggests that the connectivity of individuals as a social capital fundamentally changes the gaming environment. Our model, therefore, provides a theoretical framework for further understanding the social gaming networks.

Effect of a large gaming neighborhood and a strategy adaptation neighborhood for bolstering network reciprocity in a prisoner's dilemma game

NASA Astrophysics Data System (ADS)

Ogasawara, Takashi; Tanimoto, Jun; Fukuda, Eriko; Hagishima, Aya; Ikegaya, Naoki

2014-12-01

In 2 × 2 prisoner's dilemma (PD) games, network reciprocity is one mechanism for adding social viscosity, leading to a cooperative equilibrium. In this paper, we explain how gaming neighborhoods and strategy-adaptation neighborhoods affect network reciprocity independently in spatial PD games. We explore an appropriate range of strategy adaptation neighborhoods as opposed to the conventional method of making the gaming and strategy adaptation neighborhoods coincide to enhance the level of cooperation. In cases of expanding gaming neighborhoods, network reciprocity falls to a low level relative to the conventional setting. In the discussion below, which is based on the results of our simulation, we explore how these enhancements come about. Essentially, varying the range of the neighborhoods influences how cooperative clusters form and expand in the evolutionary process.

An Extended N-Player Network Game and Simulation of Four Investment Strategies on a Complex Innovation Network

PubMed Central

Zhou, Wen; Koptyug, Nikita; Ye, Shutao; Jia, Yifan; Lu, Xiaolong

2016-01-01

As computer science and complex network theory develop, non-cooperative games and their formation and application on complex networks have been important research topics. In the inter-firm innovation network, it is a typical game behavior for firms to invest in their alliance partners. Accounting for the possibility that firms can be resource constrained, this paper analyzes a coordination game using the Nash bargaining solution as allocation rules between firms in an inter-firm innovation network. We build an extended inter-firm n-player game based on nonidealized conditions, describe four investment strategies and simulate the strategies on an inter-firm innovation network in order to compare their performance. By analyzing the results of our experiments, we find that our proposed greedy strategy is the best-performing in most situations. We hope this study provides a theoretical insight into how firms make investment decisions. PMID:26745375

An Extended N-Player Network Game and Simulation of Four Investment Strategies on a Complex Innovation Network.

PubMed

Zhou, Wen; Koptyug, Nikita; Ye, Shutao; Jia, Yifan; Lu, Xiaolong

2016-01-01

As computer science and complex network theory develop, non-cooperative games and their formation and application on complex networks have been important research topics. In the inter-firm innovation network, it is a typical game behavior for firms to invest in their alliance partners. Accounting for the possibility that firms can be resource constrained, this paper analyzes a coordination game using the Nash bargaining solution as allocation rules between firms in an inter-firm innovation network. We build an extended inter-firm n-player game based on nonidealized conditions, describe four investment strategies and simulate the strategies on an inter-firm innovation network in order to compare their performance. By analyzing the results of our experiments, we find that our proposed greedy strategy is the best-performing in most situations. We hope this study provides a theoretical insight into how firms make investment decisions.

Contribution inequality in the spatial public goods game: Should the rich contribute more?

NASA Astrophysics Data System (ADS)

Tu, Jing

2018-04-01

Scale-free property exists in resource distribution, and the rich pay more in public goods is commonplace in reality. What will happen if the rich are expected to contribute more in the spatial public goods game? This paper therefore proposes a new contribution paradigm, in which individual contribution is determined by his payoff in the last evolution step. Tunable parameter w is used to characterize the contribution rate of nodes whose payoff is larger than the average. The results of simulations reveal that the impact of w on cooperation is associated with the enhancement factor r. When r is low, the higher w is, the lower the cooperation rate is. With the increment of r, the value of w to optimize cooperation rate increases with r. The relationship of cooperation rate and wealth on the network has also been investigated. Interestingly, higher cooperation rate does not always lead to higher wealth. Finally, the impact of w on the wealth distribution on the network is explored. The higher w reduces the inequality in wealth distribution by the shrinking of lower-class, which is enhanced by a higher r.

Challenges of Health Games in the Social Network Environment.

PubMed

Paredes, Hugo; Pinho, Anabela; Zagalo, Nelson

2012-04-01

Virtual communities and their benefits have been widely exploited to support patients, caregivers, families, and healthcare providers. The complexity of the social organization evolved the concept of virtual community to social networks, exploring the establishment of ties and relations between people. These technological platforms provide a way to keep up with one's connections network, through a set of communication and interaction tools. Games, as social interactive technologies, have great potential, ensuring a supportive community and thereby reducing social isolation. Serious social health games bring forward several research challenges. This article examines the potential benefits of the triad "health-serious games-social networks" and discusses some research challenges and opportunities of the liaison of serious health games and social networks.

Violence-related content in video game may lead to functional connectivity changes in brain networks as revealed by fMRI-ICA in young men.

PubMed

Zvyagintsev, M; Klasen, M; Weber, R; Sarkheil, P; Esposito, F; Mathiak, K A; Schwenzer, M; Mathiak, K

2016-04-21

In violent video games, players engage in virtual aggressive behaviors. Exposure to virtual aggressive behavior induces short-term changes in players' behavior. In a previous study, a violence-related version of the racing game "Carmageddon TDR2000" increased aggressive affects, cognitions, and behaviors compared to its non-violence-related version. This study investigates the differences in neural network activity during the playing of both versions of the video game. Functional magnetic resonance imaging (fMRI) recorded ongoing brain activity of 18 young men playing the violence-related and the non-violence-related version of the video game Carmageddon. Image time series were decomposed into functional connectivity (FC) patterns using independent component analysis (ICA) and template-matching yielded a mapping to established functional brain networks. The FC patterns revealed a decrease in connectivity within 6 brain networks during the violence-related compared to the non-violence-related condition: three sensory-motor networks, the reward network, the default mode network (DMN), and the right-lateralized frontoparietal network. Playing violent racing games may change functional brain connectivity, in particular and even after controlling for event frequency, in the reward network and the DMN. These changes may underlie the short-term increase of aggressive affects, cognitions, and behaviors as observed after playing violent video games. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

A Game-Theoretic Response Strategy for Coordinator Attack in Wireless Sensor Networks

PubMed Central

Liu, Jianhua; Yue, Guangxue; Shang, Huiliang; Li, Hongjie

2014-01-01

The coordinator is a specific node that controls the whole network and has a significant impact on the performance in cooperative multihop ZigBee wireless sensor networks (ZWSNs). However, the malicious node attacks coordinator nodes in an effort to waste the resources and disrupt the operation of the network. Attacking leads to a failure of one round of communication between the source nodes and destination nodes. Coordinator selection is a technique that can considerably defend against attack and reduce the data delivery delay, and increase network performance of cooperative communications. In this paper, we propose an adaptive coordinator selection algorithm using game and fuzzy logic aiming at both minimizing the average number of hops and maximizing network lifetime. The proposed game model consists of two interrelated formulations: a stochastic game for dynamic defense and a best response policy using evolutionary game formulation for coordinator selection. The stable equilibrium best policy to response defense is obtained from this game model. It is shown that the proposed scheme can improve reliability and save energy during the network lifetime with respect to security. PMID:25105171

A game-theoretic response strategy for coordinator attack in wireless sensor networks.

PubMed

Liu, Jianhua; Yue, Guangxue; Shen, Shigen; Shang, Huiliang; Li, Hongjie

2014-01-01

The coordinator is a specific node that controls the whole network and has a significant impact on the performance in cooperative multihop ZigBee wireless sensor networks (ZWSNs). However, the malicious node attacks coordinator nodes in an effort to waste the resources and disrupt the operation of the network. Attacking leads to a failure of one round of communication between the source nodes and destination nodes. Coordinator selection is a technique that can considerably defend against attack and reduce the data delivery delay, and increase network performance of cooperative communications. In this paper, we propose an adaptive coordinator selection algorithm using game and fuzzy logic aiming at both minimizing the average number of hops and maximizing network lifetime. The proposed game model consists of two interrelated formulations: a stochastic game for dynamic defense and a best response policy using evolutionary game formulation for coordinator selection. The stable equilibrium best policy to response defense is obtained from this game model. It is shown that the proposed scheme can improve reliability and save energy during the network lifetime with respect to security.

Clustering in large networks does not promote upstream reciprocity.

PubMed

Masuda, Naoki

2011-01-01

Upstream reciprocity (also called generalized reciprocity) is a putative mechanism for cooperation in social dilemma situations with which players help others when they are helped by somebody else. It is a type of indirect reciprocity. Although upstream reciprocity is often observed in experiments, most theories suggest that it is operative only when players form short cycles such as triangles, implying a small population size, or when it is combined with other mechanisms that promote cooperation on their own. An expectation is that real social networks, which are known to be full of triangles and other short cycles, may accommodate upstream reciprocity. In this study, I extend the upstream reciprocity game proposed for a directed cycle by Boyd and Richerson to the case of general networks. The model is not evolutionary and concerns the conditions under which the unanimity of cooperative players is a Nash equilibrium. I show that an abundance of triangles or other short cycles in a network does little to promote upstream reciprocity. Cooperation is less likely for a larger population size even if triangles are abundant in the network. In addition, in contrast to the results for evolutionary social dilemma games on networks, scale-free networks lead to less cooperation than networks with a homogeneous degree distribution.

Clustering in Large Networks Does Not Promote Upstream Reciprocity

PubMed Central

Masuda, Naoki

2011-01-01

Upstream reciprocity (also called generalized reciprocity) is a putative mechanism for cooperation in social dilemma situations with which players help others when they are helped by somebody else. It is a type of indirect reciprocity. Although upstream reciprocity is often observed in experiments, most theories suggest that it is operative only when players form short cycles such as triangles, implying a small population size, or when it is combined with other mechanisms that promote cooperation on their own. An expectation is that real social networks, which are known to be full of triangles and other short cycles, may accommodate upstream reciprocity. In this study, I extend the upstream reciprocity game proposed for a directed cycle by Boyd and Richerson to the case of general networks. The model is not evolutionary and concerns the conditions under which the unanimity of cooperative players is a Nash equilibrium. I show that an abundance of triangles or other short cycles in a network does little to promote upstream reciprocity. Cooperation is less likely for a larger population size even if triangles are abundant in the network. In addition, in contrast to the results for evolutionary social dilemma games on networks, scale-free networks lead to less cooperation than networks with a homogeneous degree distribution. PMID:21998641

Multi Agent Systems with Symbiotic Learning and Evolution using GNP

NASA Astrophysics Data System (ADS)

Eguchi, Toru; Hirasawa, Kotaro; Hu, Jinglu; Murata, Junichi

Recently, various attempts relevant to Multi Agent Systems (MAS) which is one of the most promising systems based on Distributed Artificial Intelligence have been studied to control large and complicated systems efficiently. In these trends of MAS, Multi Agent Systems with Symbiotic Learning and Evolution named Masbiole has been proposed. In Masbiole, symbiotic phenomena among creatures are considered in the process of learning and evolution of MAS. So we can expect more flexible and sophisticated solutions than conventional MAS. In this paper, we apply Masbiole to Iterative Prisoner’s Dilemma Games (IPD Games) using Genetic Network Programming (GNP) which is a newly developed evolutionary computation method for constituting agents. Some characteristics of Masbiole using GNP in IPD Games are clarified.

Youth, friendship, and gaming: a network perspective.

PubMed

De Grove, Frederik

2014-09-01

With digital games being part of the leisure of a multitude of young people, it is important to understand to what extent gaming-related practices such as talking about games or playing games together are associated with the quality of friendship relations with players and nonplayers. Based on 100 friendship networks, this study explored to what extent those practices permeated the everyday life of youngsters and whether they could be considered as a part of doing friendship. Results indicated that gaming as a conversational topic was widespread within and between networks. Furthermore, regardless of gender, this was significantly associated with friendship quality in almost all of the networks. When considering playing games together, a somewhat different picture emerged. In contrast to conversational practices, playing together was less widespread. Moreover, both the occurrence and the effect of co-play and friendship quality was gendered. The findings of this study show that a focus on gaming-related practices yields a fruitful starting point when considering the role of digital games in a social context that is not limited to people playing (online) games. Furthermore, they also feed into the ongoing debate of possible effects of digital games in that it shows that the way in which games influence the lives of young people goes beyond a direct effects approach.

Network characteristics for server selection in online games

NASA Astrophysics Data System (ADS)

Claypool, Mark

2008-01-01

Online gameplay is impacted by the network characteristics of players connected to the same server. Unfortunately, the network characteristics of online game servers are not well-understood, particularly for groups that wish to play together on the same server. As a step towards a remedy, this paper presents analysis of an extensive set of measurements of game servers on the Internet. Over the course of many months, actual Internet game servers were queried simultaneously by twenty-five emulated game clients, with both servers and clients spread out on the Internet. The data provides statistics on the uptime and populations of game servers over a month long period an an in-depth look at the suitability for game servers for multi-player server selection, concentrating on characteristics critical to playability--latency and fairness. Analysis finds most game servers have latencies suitable for third-person and omnipresent games, such as real-time strategy, sports and role-playing games, providing numerous server choices for game players. However, far fewer game servers have the low latencies required for first-person games, such as shooters or race games. In all cases, groups that wish to play together have a greatly reduced set of servers from which to choose because of inherent unfairness in server latencies and server selection is particularly limited as the group size increases. These results hold across different game types and even across different generations of games. The data should be useful for game developers and network researchers that seek to improve game server selection, whether for single or multiple players.

The game of go as a complex network

NASA Astrophysics Data System (ADS)

Georgeot, Bertrand; Giraud, Olivier; Kandiah, Vivek

2014-03-01

We have studied the game of go, one of the most ancient and complex board games, from a complex network perspective. We have defined a proper categorization of moves taking into account the local environment, and shown that in this case Zipf's law emerges from data taken from real games. The network shows differences between professional and amateur games, different level of amateurs, or different phases of the game. Certain eigenvectors are localized on specific groups of moves which correspond to different strategies (communities of moves). The point of view developed should allow to better modelize such games and could also help to design simulators which could in the future beat good human players. Our approach could be used for other types of games, and in parallel shed light on the human decision making process.

Properties of a new small-world network with spatially biased random shortcuts

NASA Astrophysics Data System (ADS)

Matsuzawa, Ryo; Tanimoto, Jun; Fukuda, Eriko

2017-11-01

This paper introduces a small-world (SW) network with a power-law distance distribution that differs from conventional models in that it uses completely random shortcuts. By incorporating spatial constraints, we analyze the divergence of the proposed model from conventional models in terms of fundamental network properties such as clustering coefficient, average path length, and degree distribution. We find that when the spatial constraint more strongly prohibits a long shortcut, the clustering coefficient is improved and the average path length increases. We also analyze the spatial prisoner's dilemma (SPD) games played on our new SW network in order to understand its dynamical characteristics. Depending on the basis graph, i.e., whether it is a one-dimensional ring or a two-dimensional lattice, and the parameter controlling the prohibition of long-distance shortcuts, the emergent results can vastly differ.

Interference Mitigation for Cyber-Physical Wireless Body Area Network System Using Social Networks.

PubMed

Zhang, Zhaoyang; Wang, Honggang; Wang, Chonggang; Fang, Hua

2013-06-01

Wireless body area networks (WBANs) are cyber-physical systems (CPS) that have emerged as a key technology to provide real-time health monitoring and ubiquitous healthcare services. WBANs could operate in dense environments such as in a hospital and lead to a high mutual communication interference in many application scenarios. The excessive interferences will significantly degrade the network performance including depleting the energy of WBAN nodes more quickly, and even eventually jeopardize people's lives due to unreliable (caused by the interference) healthcare data collections. Therefore, It is critical to mitigate the interference among WBANs to increase the reliability of the WBAN system while minimizing the system power consumption. Many existing approaches can deal with communication interference mitigation in general wireless networks but are not suitable for WBANs due to their ignoring the social nature of WBANs. Unlike the previous research, we for the first time propose a power game based approach to mitigate the communication interferences for WBANs based on the people's social interaction information. Our major contributions include: (1) model the inter-WBANs interference, and determine the distance distribution of the interference through both theoretical analysis and Monte Carlo simulations; (2) develop social interaction detection and prediction algorithms for people carrying WBANs; (3) develop a power control game based on the social interaction information to maximize the system's utility while minimize the energy consumption of WBANs system. The extensive simulation results show the effectiveness of the power control game for inter-WBAN interference mitigation using social interaction information. Our research opens a new research vista of WBANs using social networks.

Interference Mitigation for Cyber-Physical Wireless Body Area Network System Using Social Networks

PubMed Central

Zhang, Zhaoyang; Wang, Honggang; Wang, Chonggang; Fang, Hua

2014-01-01

Wireless body area networks (WBANs) are cyber-physical systems (CPS) that have emerged as a key technology to provide real-time health monitoring and ubiquitous healthcare services. WBANs could operate in dense environments such as in a hospital and lead to a high mutual communication interference in many application scenarios. The excessive interferences will significantly degrade the network performance including depleting the energy of WBAN nodes more quickly, and even eventually jeopardize people’s lives due to unreliable (caused by the interference) healthcare data collections. Therefore, It is critical to mitigate the interference among WBANs to increase the reliability of the WBAN system while minimizing the system power consumption. Many existing approaches can deal with communication interference mitigation in general wireless networks but are not suitable for WBANs due to their ignoring the social nature of WBANs. Unlike the previous research, we for the first time propose a power game based approach to mitigate the communication interferences for WBANs based on the people’s social interaction information. Our major contributions include: (1) model the inter-WBANs interference, and determine the distance distribution of the interference through both theoretical analysis and Monte Carlo simulations; (2) develop social interaction detection and prediction algorithms for people carrying WBANs; (3) develop a power control game based on the social interaction information to maximize the system’s utility while minimize the energy consumption of WBANs system. The extensive simulation results show the effectiveness of the power control game for inter-WBAN interference mitigation using social interaction information. Our research opens a new research vista of WBANs using social networks. PMID:25436180

Social network games uncovered: motivations and their attitudinal and behavioral outcomes.

PubMed

Lee, Jieun; Lee, Mira; Choi, In Hyok

2012-12-01

This study explores motivations for playing games on social network sites as well as attitudinal and behavioral outcomes of those motivations. A total of 324 college students in the United States participated in an online survey. Found were the six motivations for playing social network games (SNG): social interaction, self-presentation, fantasy/role playing, passing time/escapism, entertainment, and challenge/competition. Further, the findings demonstrated that different types of motivations influenced attitudes toward playing SNG and intentions to engage in different social network gaming activities differentially.

Distributed Observer Network (DON), Version 3.0, User's Guide

NASA Technical Reports Server (NTRS)

Mazzone, Rebecca A.; Conroy, Michael P.

2015-01-01

The Distributed Observer Network (DON) is a data presentation tool developed by the National Aeronautics and Space Administration (NASA) to distribute and publish simulation results. Leveraging the display capabilities inherent in modern gaming technology, DON places users in a fully navigable 3-D environment containing graphical models and allows the users to observe how those models evolve and interact over time in a given scenario. Each scenario is driven with data that has been generated by authoritative NASA simulation tools and exported in accordance with a published data interface specification. This decoupling of the data from the source tool enables DON to faithfully display a simulator's results and ensure that every simulation stakeholder will view the exact same information every time.

Application of artificial neural networks to gaming

NASA Astrophysics Data System (ADS)

Baba, Norio; Kita, Tomio; Oda, Kazuhiro

1995-04-01

Recently, neural network technology has been applied to various actual problems. It has succeeded in producing a large number of intelligent systems. In this article, we suggest that it could be applied to the field of gaming. In particular, we suggest that the neural network model could be used to mimic players' characters. Several computer simulation results using a computer gaming system which is a modified version of the COMMONS GAME confirm our idea.

Imbalanced functional link between executive control network and reward network explain the online-game seeking behaviors in Internet gaming disorder.

PubMed

Dong, Guangheng; Lin, Xiao; Hu, Yanbo; Xie, Chunming; Du, Xiaoxia

2015-03-17

Literatures have shown that Internet gaming disorder (IGD) subjects show impaired executive control and enhanced reward sensitivities than healthy controls. However, how these two networks jointly affect the valuation process and drive IGD subjects' online-game-seeking behaviors remains unknown. Thirty-five IGD and 36 healthy controls underwent a resting-states scan in the MRI scanner. Functional connectivity (FC) was examined within control and reward network seeds regions, respectively. Nucleus accumbens (NAcc) was selected as the node to find the interactions between these two networks. IGD subjects show decreased FC in the executive control network and increased FC in the reward network when comparing with the healthy controls. When examining the correlations between the NAcc and the executive control/reward networks, the link between the NAcc - executive control network is negatively related with the link between NAcc - reward network. The changes (decrease/increase) in IGD subjects' brain synchrony in control/reward networks suggest the inefficient/overly processing within neural circuitry underlying these processes. The inverse proportion between control network and reward network in IGD suggest that impairments in executive control lead to inefficient inhibition of enhanced cravings to excessive online game playing. This might shed light on the mechanistic understanding of IGD.

Sparse cliques trump scale-free networks in coordination and competition

PubMed Central

Gianetto, David A.; Heydari, Babak

2016-01-01

Cooperative behavior, a natural, pervasive and yet puzzling phenomenon, can be significantly enhanced by networks. Many studies have shown how global network characteristics affect cooperation; however, it is difficult to understand how this occurs based on global factors alone, low-level network building blocks, or motifs are necessary. In this work, we systematically alter the structure of scale-free and clique networks and show, through a stochastic evolutionary game theory model, that cooperation on cliques increases linearly with community motif count. We further show that, for reactive stochastic strategies, network modularity improves cooperation in the anti-coordination Snowdrift game and the Prisoner’s Dilemma game but not in the Stag Hunt coordination game. We also confirm the negative effect of the scale-free graph on cooperation when effective payoffs are used. On the flip side, clique graphs are highly cooperative across social environments. Adding cycles to the acyclic scale-free graph increases cooperation when multiple games are considered; however, cycles have the opposite effect on how forgiving agents are when playing the Prisoner’s Dilemma game. PMID:26899456

Sparse cliques trump scale-free networks in coordination and competition

NASA Astrophysics Data System (ADS)

Gianetto, David A.; Heydari, Babak

2016-02-01

Cooperative behavior, a natural, pervasive and yet puzzling phenomenon, can be significantly enhanced by networks. Many studies have shown how global network characteristics affect cooperation; however, it is difficult to understand how this occurs based on global factors alone, low-level network building blocks, or motifs are necessary. In this work, we systematically alter the structure of scale-free and clique networks and show, through a stochastic evolutionary game theory model, that cooperation on cliques increases linearly with community motif count. We further show that, for reactive stochastic strategies, network modularity improves cooperation in the anti-coordination Snowdrift game and the Prisoner’s Dilemma game but not in the Stag Hunt coordination game. We also confirm the negative effect of the scale-free graph on cooperation when effective payoffs are used. On the flip side, clique graphs are highly cooperative across social environments. Adding cycles to the acyclic scale-free graph increases cooperation when multiple games are considered; however, cycles have the opposite effect on how forgiving agents are when playing the Prisoner’s Dilemma game.

Collectives for Multiple Resource Job Scheduling Across Heterogeneous Servers

NASA Technical Reports Server (NTRS)

Tumer, K.; Lawson, J.

2003-01-01

Efficient management of large-scale, distributed data storage and processing systems is a major challenge for many computational applications. Many of these systems are characterized by multi-resource tasks processed across a heterogeneous network. Conventional approaches, such as load balancing, work well for centralized, single resource problems, but breakdown in the more general case. In addition, most approaches are often based on heuristics which do not directly attempt to optimize the world utility. In this paper, we propose an agent based control system using the theory of collectives. We configure the servers of our network with agents who make local job scheduling decisions. These decisions are based on local goals which are constructed to be aligned with the objective of optimizing the overall efficiency of the system. We demonstrate that multi-agent systems in which all the agents attempt to optimize the same global utility function (team game) only marginally outperform conventional load balancing. On the other hand, agents configured using collectives outperform both team games and load balancing (by up to four times for the latter), despite their distributed nature and their limited access to information.

Signalling chains with probe and adjust learning

NASA Astrophysics Data System (ADS)

Gosti, Giorgio

2018-04-01

Many models explain the evolution of signalling in repeated stage games on social networks, differently in this study each signalling game evolves a communication strategy to transmit information across the network. Specifically, I formalise signalling chain games as a generalisation of Lewis' signalling games, where a number of players are placed on a chain network and play a signalling game in which they have to propagate information across the network. I show that probe and adjust learning allows the system to develop communication conventions, but it may temporarily perturb the system out of conventions. Through simulations, I evaluate how long the system takes to evolve a signalling convention and the amount of time it stays in it. This discussion presents a mechanism in which simple players can evolve signalling across a social network without necessarily understanding the entire system.

Impact of heterogeneous activity and community structure on the evolutionary success of cooperators in social networks

NASA Astrophysics Data System (ADS)

Wu, Zhi-Xi; Rong, Zhihai; Yang, Han-Xin

2015-01-01

Recent empirical studies suggest that heavy-tailed distributions of human activities are universal in real social dynamics [L. Muchnik, S. Pei, L. C. Parra, S. D. S. Reis, J. S. Andrade Jr., S. Havlin, and H. A. Makse, Sci. Rep. 3, 1783 (2013), 10.1038/srep01783]. On the other hand, community structure is ubiquitous in biological and social networks [M. E. J. Newman, Nat. Phys. 8, 25 (2012), 10.1038/nphys2162]. Motivated by these facts, we here consider the evolutionary prisoner's dilemma game taking place on top of a real social network to investigate how the community structure and the heterogeneity in activity of individuals affect the evolution of cooperation. In particular, we account for a variation of the birth-death process (which can also be regarded as a proportional imitation rule from a social point of view) for the strategy updating under both weak and strong selection (meaning the payoffs harvested from games contribute either slightly or heavily to the individuals' performance). By implementing comparative studies, where the players are selected either randomly or in terms of their actual activities to play games with their immediate neighbors, we figure out that heterogeneous activity benefits the emergence of collective cooperation in a harsh environment (the action for cooperation is costly) under strong selection, whereas it impairs the formation of altruism under weak selection. Moreover, we find that the abundance of communities in the social network can evidently foster the formation of cooperation under strong selection, in contrast to the games evolving on randomized counterparts. Our results are therefore helpful for us to better understand the evolution of cooperation in real social systems.

Local Voltage Control in Distribution Networks: A Game-Theoretic Perspective

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Xinyang; Tian, Jie; Chen, Lijun

Inverter-based voltage regulation is gaining importance to alleviate emerging reliability and power-quality concerns related to distribution systems with high penetration of photovoltaic (PV) systems. This paper seeks contribution in the domain of reactive power compensation by establishing stability of local Volt/VAr controllers. In lieu of the approximate linear surrogate used in the existing work, the paper establishes existence and uniqueness of an equilibrium point using nonlinear AC power flow model. Key to this end is to consider a nonlinear dynamical system with non-incremental local Volt/VAr control, cast the Volt/VAr dynamics as a game, and leverage the fixed-point theorem as wellmore » as pertinent contraction mapping argument. Numerical examples are provided to complement the analytical results.« less

Local Voltage Control in Distribution Networks: A Game-Theoretic Perspective: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Xinyang; Tian, Jie; Chen, Lijun

Inverter-based voltage regulation is gaining importance to alleviate emerging reliability and power-quality concerns related to distribution systems with high penetration of photovoltaic (PV) systems. This paper seeks contribution in the domain of reactive power compensation by establishing stability of local Volt/VAr controllers. In lieu of the approximate linear surrogate used in the existing work, the paper establishes existence and uniqueness of an equilibrium point using nonlinear AC power flow model. Key to this end is to consider a nonlinear dynamical system with non-incremental local Volt/VAr control, cast the Volt/VAr dynamics as a game, and leverage the fixed-point theorem as wellmore » as pertinent contraction mapping argument. Numerical examples are provided to complement the analytical results.« less

Quantum games on evolving random networks

NASA Astrophysics Data System (ADS)

Pawela, Łukasz

2016-09-01

We study the advantages of quantum strategies in evolutionary social dilemmas on evolving random networks. We focus our study on the two-player games: prisoner's dilemma, snowdrift and stag-hunt games. The obtained result show the benefits of quantum strategies for the prisoner's dilemma game. For the other two games, we obtain regions of parameters where the quantum strategies dominate, as well as regions where the classical strategies coexist.

Social dilemmas in an online social network: The structure and evolution of cooperation

NASA Astrophysics Data System (ADS)

Fu, Feng; Chen, Xiaojie; Liu, Lianghuan; Wang, Long

2007-11-01

We investigate two paradigms for studying the evolution of cooperation—Prisoner's Dilemma and Snowdrift game in an online friendship network, obtained from a social networking site. By structural analysis, it is revealed that the empirical social network has small-world and scale-free properties. Besides, it exhibits assortative mixing pattern. Then, we study the evolutionary version of the two types of games on it. It is found that cooperation is substantially promoted with small values of game matrix parameters in both games. Whereas the competent cooperators induced by the underlying network of contacts will be dramatically inhibited with increasing values of the game parameters. Further, we explore the role of assortativity in evolution of cooperation by random edge rewiring. We find that increasing amount of assortativity will to a certain extent diminish the cooperation level. We also show that connected large hubs are capable of maintaining cooperation. The evolution of cooperation on empirical networks is influenced by various network effects in a combined manner, compared with that on model networks. Our results can help understand the cooperative behaviors in human groups and society.

A study on haptic collaborative game in shared virtual environment

NASA Astrophysics Data System (ADS)

Lu, Keke; Liu, Guanyang; Liu, Lingzhi

2013-03-01

A study on collaborative game in shared virtual environment with haptic feedback over computer networks is introduced in this paper. A collaborative task was used where the players located at remote sites and played the game together. The player can feel visual and haptic feedback in virtual environment compared to traditional networked multiplayer games. The experiment was desired in two conditions: visual feedback only and visual-haptic feedback. The goal of the experiment is to assess the impact of force feedback on collaborative task performance. Results indicate that haptic feedback is beneficial for performance enhancement for collaborative game in shared virtual environment. The outcomes of this research can have a powerful impact on the networked computer games.

Stochastic Dual Algorithm for Voltage Regulation in Distribution Networks with Discrete Loads: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dall-Anese, Emiliano; Zhou, Xinyang; Liu, Zhiyuan

This paper considers distribution networks with distributed energy resources and discrete-rate loads, and designs an incentive-based algorithm that allows the network operator and the customers to pursue given operational and economic objectives, while concurrently ensuring that voltages are within prescribed limits. Four major challenges include: (1) the non-convexity from discrete decision variables, (2) the non-convexity due to a Stackelberg game structure, (3) unavailable private information from customers, and (4) different update frequency from two types of devices. In this paper, we first make convex relaxation for discrete variables, then reformulate the non-convex structure into a convex optimization problem together withmore » pricing/reward signal design, and propose a distributed stochastic dual algorithm for solving the reformulated problem while restoring feasible power rates for discrete devices. By doing so, we are able to statistically achieve the solution of the reformulated problem without exposure of any private information from customers. Stability of the proposed schemes is analytically established and numerically corroborated.« less

Kinect Technology Game Play to Mimic Quake Catcher Network (QCN) Sensor Deployment During a Rapid Aftershock Mobilization Program (RAMP)

NASA Astrophysics Data System (ADS)

Kilb, D. L.; Yang, A.; Rohrlick, D.; Cochran, E. S.; Lawrence, J.; Chung, A. I.; Neighbors, C.; Choo, Y.

2011-12-01

The Kinect technology allows for hands-free game play, greatly increasing the accessibility of gaming for those uncomfortable using controllers. How it works is the Kinect camera transmits invisible near-infrared light and measures its "time of flight" to reflect off an object, allowing it to distinguish objects within 1 centimeter in depth and 3 mm in height and width. The middleware can also respond to body gestures and voice commands. Here, we use the Kinect Windows SDK software to create a game that mimics how scientists deploy seismic instruments following a large earthquake. The educational goal of the game is to allow the players to explore 3D space as they learn about the Quake Catcher Network's (QCN) Rapid Aftershock Mobilization Program (RAMP). Many of the scenarios within the game are taken from factual RAMP experiences. To date, only the PC platform (or a Mac running PC emulator software) is available for use, but we hope to move to other platforms (e.g., Xbox 360, iPad, iPhone) as they become available. The game is written in programming language C# using Microsoft XNA and Visual Studio 2010, graphic shading is added using High Level Shader Language (HLSL), and rendering is produced using XNA's graphics libraries. Key elements of the game include selecting sensor locations, adequately installing the sensor, and monitoring the incoming data. During game play aftershocks can occur unexpectedly, as can other problems that require attention (e.g., power outages, equipment failure, and theft). The player accrues points for quickly deploying the first sensor (recording as many initial aftershocks as possible), correctly installing the sensors (orientation with respect to north, properly securing, and testing), distributing the sensors adequately in the region, and troubleshooting problems. One can also net points for efficient use of game play time. Setting up for game play in your local environment requires: (1) the Kinect hardware ( $145); (2) a computer with a Windows operating system (Mac users can use a Windows emulator); and (3) our free QCN game software (available from http://quakeinfo.ucsd.edu/ dkilb/WEB/QCN/Downloads.html).

A unified framework for the pareto law and Matthew effect using scale-free networks

NASA Astrophysics Data System (ADS)

Hu, M.-B.; Wang, W.-X.; Jiang, R.; Wu, Q.-S.; Wang, B.-H.; Wu, Y.-H.

2006-09-01

We investigate the accumulated wealth distribution by adopting evolutionary games taking place on scale-free networks. The system self-organizes to a critical Pareto distribution (1897) of wealth P(m)˜m-(v+1) with 1.6 < v <2.0 (which is in agreement with that of U.S. or Japan). Particularly, the agent's personal wealth is proportional to its number of contacts (connectivity), and this leads to the phenomenon that the rich gets richer and the poor gets relatively poorer, which is consistent with the Matthew Effect present in society, economy, science and so on. Though our model is simple, it provides a good representation of cooperation and profit accumulation behavior in economy, and it combines the network theory with econophysics.

Maximum Power Game as a Physical and Social Extension of Classical Games

NASA Astrophysics Data System (ADS)

Kim, Pilwon

2017-03-01

We consider an electric circuit in which the players participate as resistors and adjust their resistance in pursuit of individual maximum power. The maximum power game(MPG) becomes very complicated in a circuit which is indecomposable into serial/parallel components, yielding a nontrivial power distribution at equilibrium. Depending on the circuit topology, MPG covers a wide range of phenomena: from a social dilemma in which the whole group loses to a well-coordinated situation in which the individual pursuit of power promotes the collective outcomes. We also investigate a situation where each player in the circuit has an intrinsic heat waste. Interestingly, it is this individual inefficiency which can keep them from the collective failure in power generation. When coping with an efficient opponent with small intrinsic resistance, a rather inefficient player gets more power than efficient one. A circuit with multiple voltage inputs forms the network-based maximum power game. One of our major interests is to figure out, in what kind of the networks the pursuit for private power leads to greater total power. It turns out that the circuits with the scale-free structure is one of the good candidates which generates as much power as close to the possible maximum total.

Stochastic noncooperative and cooperative evolutionary game strategies of a population of biological networks under natural selection.

PubMed

Chen, Bor-Sen; Yeh, Chin-Hsun

2017-12-01

We review current static and dynamic evolutionary game strategies of biological networks and discuss the lack of random genetic variations and stochastic environmental disturbances in these models. To include these factors, a population of evolving biological networks is modeled as a nonlinear stochastic biological system with Poisson-driven genetic variations and random environmental fluctuations (stimuli). To gain insight into the evolutionary game theory of stochastic biological networks under natural selection, the phenotypic robustness and network evolvability of noncooperative and cooperative evolutionary game strategies are discussed from a stochastic Nash game perspective. The noncooperative strategy can be transformed into an equivalent multi-objective optimization problem and is shown to display significantly improved network robustness to tolerate genetic variations and buffer environmental disturbances, maintaining phenotypic traits for longer than the cooperative strategy. However, the noncooperative case requires greater effort and more compromises between partly conflicting players. Global linearization is used to simplify the problem of solving nonlinear stochastic evolutionary games. Finally, a simple stochastic evolutionary model of a metabolic pathway is simulated to illustrate the procedure of solving for two evolutionary game strategies and to confirm and compare their respective characteristics in the evolutionary process. Copyright © 2017 Elsevier B.V. All rights reserved.

Evolutionary prisoner's dilemma on Newman-Watts social networks with an asymmetric payoff distribution mechanism

NASA Astrophysics Data System (ADS)

Du, Wen-Bo; Cao, Xian-Bin; Yang, Han-Xin; Hu, Mao-Bin

2010-01-01

In this paper, we introduce an asymmetric payoff distribution mechanism into the evolutionary prisoner's dilemma game (PDG) on Newman-Watts social networks, and study its effects on the evolution of cooperation. The asymmetric payoff distribution mechanism can be adjusted by the parameter α: if α > 0, the rich will exploit the poor to get richer; if α < 0, the rich are forced to offer part of their income to the poor. Numerical results show that the cooperator frequency monotonously increases with α and is remarkably promoted when α > 0. The effects of updating order and self-interaction are also investigated. The co-action of random updating and self-interaction can induce the highest cooperation level. Moreover, we employ the Gini coefficient to investigate the effect of asymmetric payoff distribution on the the system's wealth distribution. This work may be helpful for understanding cooperative behaviour and wealth inequality in society.

A novel framework of classical and quantum prisoner's dilemma games on coupled networks.

PubMed

Deng, Xinyang; Zhang, Qi; Deng, Yong; Wang, Zhen

2016-03-15

Evolutionary games on multilayer networks are attracting growing interest. While among previous studies, the role of quantum games in such a infrastructure is still virgin and may become a fascinating issue across a myriad of research realms. To mimick two kinds of different interactive environments and mechanisms, in this paper a new framework of classical and quantum prisoner's dilemma games on two-layer coupled networks is considered. Within the proposed model, the impact of coupling factor of networks and entanglement degree in quantum games on the evolutionary process has been studied. Simulation results show that the entanglement has no impact on the evolution of the classical prisoner's dilemma, while the rise of the coupling factor obviously impedes cooperation in this game, and the evolution of quantum prisoner's dilemma is greatly impacted by the combined effect of entanglement and coupling.

A novel framework of classical and quantum prisoner’s dilemma games on coupled networks

PubMed Central

Deng, Xinyang; Zhang, Qi; Deng, Yong; Wang, Zhen

2016-01-01

Evolutionary games on multilayer networks are attracting growing interest. While among previous studies, the role of quantum games in such a infrastructure is still virgin and may become a fascinating issue across a myriad of research realms. To mimick two kinds of different interactive environments and mechanisms, in this paper a new framework of classical and quantum prisoner’s dilemma games on two-layer coupled networks is considered. Within the proposed model, the impact of coupling factor of networks and entanglement degree in quantum games on the evolutionary process has been studied. Simulation results show that the entanglement has no impact on the evolution of the classical prisoner’s dilemma, while the rise of the coupling factor obviously impedes cooperation in this game, and the evolution of quantum prisoner’s dilemma is greatly impacted by the combined effect of entanglement and coupling. PMID:26975447

Jamming in Mobile Networks: A Game-Theoretic Approach

DTIC Science & Technology

2013-03-01

general treatment of multiplayer differential games was presented by Starr and Ho [16], Leitmann [36], Vaisbord and Zhukovskiy [65], Zhukovskiy and...REPORT Jamming in mobile networks: A game -theoretic approach. 14. ABSTRACT 16. SECURITY CLASSIFICATION OF: In this paper, we address the problem of...model the intrusion as a pursuit-evasion game between a mobile jammer and a team of agents. First, we consider a differential game -theoretic approach

The Price of Anarchy in Network Creation Games Is (Mostly) Constant

NASA Astrophysics Data System (ADS)

Mihalák, Matúš; Schlegel, Jan Christoph

We study the price of anarchy and the structure of equilibria in network creation games. A network creation game (first defined and studied by Fabrikant et al. [4]) is played by n players {1,2,...,n}, each identified with a vertex of a graph (network), where the strategy of player i, i = 1,...,n, is to build some edges adjacent to i. The cost of building an edge is α> 0, a fixed parameter of the game. The goal of every player is to minimize its creation cost plus its usage cost. The creation cost of player i is α times the number of built edges. In the SumGame (the original variant of Fabrikant et al. [4]) the usage cost of player i is the sum of distances from i to every node of the resulting graph. In the MaxGame (variant defined and studied by Demaine et al. [3]) the usage cost is the eccentricity of i in the resulting graph of the game. In this paper we improve previously known bounds on the price of anarchy of the game (of both variants) for various ranges of α, and give new insights into the structure of equilibria for various values of α. The two main results of the paper show that for α > 273·n all equilibria in SumGame are trees and thus the price of anarchy is constant, and that for α> 129 all equilibria in MaxGame are trees and the price of anarchy is constant. For SumGame this (almost) answers one of the basic open problems in the field - is price of anarchy of the network creation game constant for all values of α? - in an affirmative way, up to a tiny range of α.

Evolution of Cooperation in Continuous Prisoner's Dilemma Games on Barabasi—Albert Networks with Degree-Dependent Guilt Mechanism

NASA Astrophysics Data System (ADS)

Wang, Xian-Jia; Quan, Ji; Liu, Wei-Bing

2012-05-01

This paper studies the continuous prisoner's dilemma games (CPDG) on Barabasi—Albert (BA) networks. In the model, each agent on a vertex of the networks makes an investment and interacts with all of his neighboring agents. Making an investment is costly, but which benefits its neighboring agents, where benefit and cost depend on the level of investment made. The payoff of each agent is given by the sum of payoffs it receives in its interactions with all its neighbors. Not only payoff, individual's guilty emotion in the games has also been considered. The negative guilty emotion produced in comparing with its neighbors can reduce the utility of individuals directly. We assume that the reduction amount depends on the individual's degree and a baseline level parameter. The group's cooperative level is characterized by the average investment of the population. Each player makes his investment in the next step based on a convex combination of the investment of his best neighbors in the last step, his best history strategies in the latest steps which number is controlled by a memory length parameter, and a uniformly distributed random number. Simulation results show that this degree-dependent guilt mechanism can promote the evolution of cooperation dramatically comparing with degree-independent guilt or no guilt cases. Imitation, memory, uncertainty coefficients and network structure also play determinant roles in the cooperation level of the population. All our results may shed some new light on studying the evolution of cooperation based on network reciprocity mechanisms.

77 FR 29637 - Game Show Network, LLC v. Cablevision Systems Corp.

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-18

... FEDERAL COMMUNICATIONS COMMISSION [MB Docket No. 12-122; File No. CSR-8529-P; DA 12-739] Game Show... Administrative Law Judge (``ALJ'') to resolve the factual disputes and to return an Initial Decision. DATES: Game... control. 6. GSN is a national cable network launched on December 1, 1994 under the name ``Game Show...

Power-efficient distributed resource allocation under goodput QoS constraints for heterogeneous networks

NASA Astrophysics Data System (ADS)

Andreotti, Riccardo; Del Fiorentino, Paolo; Giannetti, Filippo; Lottici, Vincenzo

2016-12-01

This work proposes a distributed resource allocation (RA) algorithm for packet bit-interleaved coded OFDM transmissions in the uplink of heterogeneous networks (HetNets), characterized by small cells deployed over a macrocell area and sharing the same band. Every user allocates its transmission resources, i.e., bits per active subcarrier, coding rate, and power per subcarrier, to minimize the power consumption while both guaranteeing a target quality of service (QoS) and accounting for the interference inflicted by other users transmitting over the same band. The QoS consists of the number of information bits delivered in error-free packets per unit of time, or goodput (GP), estimated at the transmitter by resorting to an efficient effective SNR mapping technique. First, the RA problem is solved in the point-to-point case, thus deriving an approximate yet accurate closed-form expression for the power allocation (PA). Then, the interference-limited HetNet case is examined, where the RA problem is described as a non-cooperative game, providing a solution in terms of generalized Nash equilibrium. Thanks to the closed-form of the PA, the solution analysis is based on the best response concept. Hence, sufficient conditions for existence and uniqueness of the solution are analytically derived, along with a distributed algorithm capable of reaching the game equilibrium.

When You Can’t Beat ’em, Join ’em: Leveraging ComplexityScience for Innovative Solutions

DTIC Science & Technology

2017-08-21

chemical reactions : • Belousov-Zhabotinskii reaction ... Engineering (ARE) Technical Interchange Meeting by: Dr. Josef Schaff, NAVAIR 4.5 DISTRIBUTION STATEMENT A • Commander’s intent: Networked Navy & the intent...Physics undergrad, software engineering jobs in comms, video games, robotics • Started NAWCAD (NADC) as a computer scientist / engineer

The Stochastic Evolutionary Game for a Population of Biological Networks Under Natural Selection

PubMed Central

Chen, Bor-Sen; Ho, Shih-Ju

2014-01-01

In this study, a population of evolutionary biological networks is described by a stochastic dynamic system with intrinsic random parameter fluctuations due to genetic variations and external disturbances caused by environmental changes in the evolutionary process. Since information on environmental changes is unavailable and their occurrence is unpredictable, they can be considered as a game player with the potential to destroy phenotypic stability. The biological network needs to develop an evolutionary strategy to improve phenotypic stability as much as possible, so it can be considered as another game player in the evolutionary process, ie, a stochastic Nash game of minimizing the maximum network evolution level caused by the worst environmental disturbances. Based on the nonlinear stochastic evolutionary game strategy, we find that some genetic variations can be used in natural selection to construct negative feedback loops, efficiently improving network robustness. This provides larger genetic robustness as a buffer against neutral genetic variations, as well as larger environmental robustness to resist environmental disturbances and maintain a network phenotypic traits in the evolutionary process. In this situation, the robust phenotypic traits of stochastic biological networks can be more frequently selected by natural selection in evolution. However, if the harbored neutral genetic variations are accumulated to a sufficiently large degree, and environmental disturbances are strong enough that the network robustness can no longer confer enough genetic robustness and environmental robustness, then the phenotype robustness might break down. In this case, a network phenotypic trait may be pushed from one equilibrium point to another, changing the phenotypic trait and starting a new phase of network evolution through the hidden neutral genetic variations harbored in network robustness by adaptive evolution. Further, the proposed evolutionary game is extended to an n-tuple evolutionary game of stochastic biological networks with m players (competitive populations) and k environmental dynamics. PMID:24558296

Mastering the game of Go with deep neural networks and tree search

NASA Astrophysics Data System (ADS)

Silver, David; Huang, Aja; Maddison, Chris J.; Guez, Arthur; Sifre, Laurent; van den Driessche, George; Schrittwieser, Julian; Antonoglou, Ioannis; Panneershelvam, Veda; Lanctot, Marc; Dieleman, Sander; Grewe, Dominik; Nham, John; Kalchbrenner, Nal; Sutskever, Ilya; Lillicrap, Timothy; Leach, Madeleine; Kavukcuoglu, Koray; Graepel, Thore; Hassabis, Demis

2016-01-01

The game of Go has long been viewed as the most challenging of classic games for artificial intelligence owing to its enormous search space and the difficulty of evaluating board positions and moves. Here we introduce a new approach to computer Go that uses ‘value networks’ to evaluate board positions and ‘policy networks’ to select moves. These deep neural networks are trained by a novel combination of supervised learning from human expert games, and reinforcement learning from games of self-play. Without any lookahead search, the neural networks play Go at the level of state-of-the-art Monte Carlo tree search programs that simulate thousands of random games of self-play. We also introduce a new search algorithm that combines Monte Carlo simulation with value and policy networks. Using this search algorithm, our program AlphaGo achieved a 99.8% winning rate against other Go programs, and defeated the human European Go champion by 5 games to 0. This is the first time that a computer program has defeated a human professional player in the full-sized game of Go, a feat previously thought to be at least a decade away.

Auction-based Security Game for Multiuser Cooperative Networks

NASA Astrophysics Data System (ADS)

Wang, An; Cai, Yueming; Yang, Wendong; Cheng, Yunpeng

2013-04-01

In this paper, we develop an auction-based algorithm to allocate the relay power efficiently to improve the system secrecy rate in a cooperative network, where several source-destination pairs and one cooperative relay are involved. On the one hand, the cooperative relay assists these pairs to transmit under a peak power constraint. On the other hand, the relay is untrusty and is also a passive eavesdropper. The whole auction process is completely distributed and no instantaneous channel state information exchange is needed. We also prove the existence and uniqueness of the Nash Equilibrium (NE) for the proposed power auction game. Moreover, the Pareto optimality is also validated. Simulation results show that our proposed auction-based algorithm can effectively improve the system secrecy rate. Besides, the proposed auction-based algorithm can converge to the unique NE point within a finite number of iterations. More interestingly, we also find that the proposed power auction mechanism is cheat-proof.

Improving Search Algorithms by Using Intelligent Coordinates

NASA Technical Reports Server (NTRS)

Wolpert, David H.; Tumer, Kagan; Bandari, Esfandiar

2004-01-01

We consider algorithms that maximize a global function G in a distributed manner, using a different adaptive computational agent to set each variable of the underlying space. Each agent eta is self-interested; it sets its variable to maximize its own function g (sub eta). Three factors govern such a distributed algorithm's performance, related to exploration/exploitation, game theory, and machine learning. We demonstrate how to exploit alI three factors by modifying a search algorithm's exploration stage: rather than random exploration, each coordinate of the search space is now controlled by a separate machine-learning-based player engaged in a noncooperative game. Experiments demonstrate that this modification improves simulated annealing (SA) by up to an order of magnitude for bin packing and for a model of an economic process run over an underlying network. These experiments also reveal interesting small-world phenomena.

Improving search algorithms by using intelligent coordinates

NASA Astrophysics Data System (ADS)

Wolpert, David; Tumer, Kagan; Bandari, Esfandiar

2004-01-01

We consider algorithms that maximize a global function G in a distributed manner, using a different adaptive computational agent to set each variable of the underlying space. Each agent η is self-interested; it sets its variable to maximize its own function gη. Three factors govern such a distributed algorithm’s performance, related to exploration/exploitation, game theory, and machine learning. We demonstrate how to exploit all three factors by modifying a search algorithm’s exploration stage: rather than random exploration, each coordinate of the search space is now controlled by a separate machine-learning-based “player” engaged in a noncooperative game. Experiments demonstrate that this modification improves simulated annealing (SA) by up to an order of magnitude for bin packing and for a model of an economic process run over an underlying network. These experiments also reveal interesting small-world phenomena.

Addressing tomorrow's DMO technical challenges today

NASA Astrophysics Data System (ADS)

Milligan, James R.

2009-05-01

Distributed Mission Operations (DMO) is essentially a type of networked training that pulls in participants from all the armed services and, increasingly, allies to permit them to "game" and rehearse highly complex campaigns, using a mix of local, distant, and virtual players. The United States Air Force Research Laboratory (AFRL) is pursuing Science and Technology (S&T) solutions to address technical challenges associated with distributed communications and information management as DMO continues to progressively scale up the number, diversity, and geographic dispersal of participants in training and rehearsal exercises.

2-Player Game With Uncertainty to Protect Mission Critical Information Over Blue Networks

DTIC Science & Technology

2009-04-01

Eclipse 233MHz 512MB 700MB JAVA 6 166MHz 64MB 98MB Key Focus Sensor Honeypot 1.5 GHz 512MB 500MB Distributed Data Pastry JAVA...defense, Pastry , run. JAVA 6 is an added plug-in that helps Eclipse software. There are many defenses that can be used to help alongside this project but...each defense to be used. Encryption : Steganos Privacy Suite 2008 Honeypots : Key Focus Sensor Distributed Data: Pastry 7    Table 2 Domain

The design of multiplayer online video game systems

NASA Astrophysics Data System (ADS)

Hsu, Chia-chun A.; Ling, Jim; Li, Qing; Kuo, C.-C. J.

2003-11-01

The distributed Multiplayer Online Game (MOG) system is complex since it involves technologies in computer graphics, multimedia, artificial intelligence, computer networking, embedded systems, etc. Due to the large scope of this problem, the design of MOG systems has not yet been widely addressed in the literatures. In this paper, we review and analyze the current MOG system architecture followed by evaluation. Furthermore, we propose a clustered-server architecture to provide a scalable solution together with the region oriented allocation strategy. Two key issues, i.e. interesting management and synchronization, are discussed in depth. Some preliminary ideas to deal with the identified problems are described.

Navigable networks as Nash equilibria of navigation games.

PubMed

Gulyás, András; Bíró, József J; Kőrösi, Attila; Rétvári, Gábor; Krioukov, Dmitri

2015-07-03

Common sense suggests that networks are not random mazes of purposeless connections, but that these connections are organized so that networks can perform their functions well. One function common to many networks is targeted transport or navigation. Here, using game theory, we show that minimalistic networks designed to maximize the navigation efficiency at minimal cost share basic structural properties with real networks. These idealistic networks are Nash equilibria of a network construction game whose purpose is to find an optimal trade-off between the network cost and navigability. We show that these skeletons are present in the Internet, metabolic, English word, US airport, Hungarian road networks, and in a structural network of the human brain. The knowledge of these skeletons allows one to identify the minimal number of edges, by altering which one can efficiently improve or paralyse navigation in the network.

Mobile and Web Game Development: Using Videogames as an Educational and Outreach Tool

NASA Technical Reports Server (NTRS)

Jaime, Fernando I.

2012-01-01

Few tools reach out to capture the imagination and interests of children like video games do. As such, the development of educational applications that foster young minds' interest in science and technology become of the utmost importance. To this end, I spent my summer internship developing outreach and educational applications in conjunction with JPL's Space Place team. This small, but dedicated, team of people manages three NASA websites that focus on presenting science and technology information in such a manner that young children can understand it and develop an interest in the subjects. Besides the websites, with their plethora of educational content presented through hands-on activities, games and informative articles, the team also creates and coordinates the distribution of printed material to museums, astronomy clubs and a huge network of educators.

Multiple effect of social influence on cooperation in interdependent network games.

PubMed

Jiang, Luo-Luo; Li, Wen-Jing; Wang, Zhen

2015-10-01

The social influence exists widely in the human society, where individual decision-making process (from congressional election to electronic commerce) may be affected by the attitude and behavior of others belonging to different social networks. Here, we couple the snowdrift (SD) game and the prisoner's dilemma (PD) game on two interdependent networks, where strategies in both games are associated by social influence to mimick the majority rule. More accurately, individuals' strategies updating refers to social learning (based on payoff difference) and above-mentioned social influence (related with environment of interdependent group), which is controlled by social influence strength s. Setting s = 0 decouples the networks and returns the traditional network game; while its increase involves the interactions between networks. By means of numerous Monte Carlo simulations, we find that such a mechanism brings multiple influence to the evolution of cooperation. Small s leads to unequal cooperation level in both games, because social learning is still the main updating rule for most players. Though intermediate and large s guarantees the synchronized evolution of strategy pairs, cooperation finally dies out and reaches a completely dominance in both cases. Interestingly, these observations are attributed to the expansion of cooperation clusters. Our work may provide a new understanding to the emergence of cooperation in intercorrelated social systems.

Multiple effect of social influence on cooperation in interdependent network games

NASA Astrophysics Data System (ADS)

Jiang, Luo-Luo; Li, Wen-Jing; Wang, Zhen

2015-10-01

The social influence exists widely in the human society, where individual decision-making process (from congressional election to electronic commerce) may be affected by the attitude and behavior of others belonging to different social networks. Here, we couple the snowdrift (SD) game and the prisoner’s dilemma (PD) game on two interdependent networks, where strategies in both games are associated by social influence to mimick the majority rule. More accurately, individuals’ strategies updating refers to social learning (based on payoff difference) and above-mentioned social influence (related with environment of interdependent group), which is controlled by social influence strength s. Setting s = 0 decouples the networks and returns the traditional network game; while its increase involves the interactions between networks. By means of numerous Monte Carlo simulations, we find that such a mechanism brings multiple influence to the evolution of cooperation. Small s leads to unequal cooperation level in both games, because social learning is still the main updating rule for most players. Though intermediate and large s guarantees the synchronized evolution of strategy pairs, cooperation finally dies out and reaches a completely dominance in both cases. Interestingly, these observations are attributed to the expansion of cooperation clusters. Our work may provide a new understanding to the emergence of cooperation in intercorrelated social systems.

Video Games, Internet and Social Networks: A Study among French School students

PubMed

Dany, Lionel; Moreau, Laure; Guillet, Clémentine; Franchina, Carmelo

2016-11-25

Aim : Screen-based media use is gradually becoming a public health issue, especially among young people.Method : A local descriptive observational study was conducted in 11 colleges of the Bouches-du-Rhône department. All middle high school students were asked to fill in a questionnaire comprising questions about their demographic characteristics, their screen-based media use (Internet, video games, social networks), any problematic use (video games and social networks), self-esteem and quality of life.Results : A total of 950 college students (mean age : 12.96 years) participated in the research. The results show a high level and a very diverse screen-based media use. Boys more frequently played video games and girls go more frequently used social networks. The levels of problematic use were relatively low for all middle high school students. The level of problematic video game use was significantly higher in boys, and the level of problematic social network use was higher in girls.Conclusion : Differences in the use of video games or social networks raise the general issue of gender differences in society. This study indicates the need for more specific preventive interventions for screen-based media use. The addictive “nature” of certain practices needs to be studied in more detail.

A game-theoretic approach to optimize ad hoc networks inspired by small-world network topology

NASA Astrophysics Data System (ADS)

Tan, Mian; Yang, Tinghong; Chen, Xing; Yang, Gang; Zhu, Guoqing; Holme, Petter; Zhao, Jing

2018-03-01

Nodes in ad hoc networks are connected in a self-organized manner. Limited communication radius makes information transmit in multi-hop mode, and each forwarding needs to consume the energy of nodes. Insufficient communication radius or exhaustion of energy may cause the absence of some relay nodes and links, further breaking network connectivity. On the other hand, nodes in the network may refuse to cooperate due to objective faulty or personal selfish, hindering regular communication in the network. This paper proposes a model called Repeated Game in Small World Networks (RGSWN). In this model, we first construct ad hoc networks with small-world feature by forming "communication shortcuts" between multiple-radio nodes. Small characteristic path length reduces average forwarding times in networks; meanwhile high clustering coefficient enhances network robustness. Such networks still maintain relative low global power consumption, which is beneficial to extend the network survival time. Then we use MTTFT strategy (Mend-Tolerance Tit-for-Tat) for repeated game as a rule for the interactions between neighbors in the small-world networks. Compared with other five strategies of repeated game, this strategy not only punishes the nodes' selfishness more reasonably, but also has the best tolerance to the network failure. This work is insightful for designing an efficient and robust ad hoc network.

Dynamic Bayesian Network Modeling of Game Based Diagnostic Assessments. CRESST Report 837

ERIC Educational Resources Information Center

Levy, Roy

2014-01-01

Digital games offer an appealing environment for assessing student proficiencies, including skills and misconceptions in a diagnostic setting. This paper proposes a dynamic Bayesian network modeling approach for observations of student performance from an educational video game. A Bayesian approach to model construction, calibration, and use in…

Spontaneous Symmetry Breaking in Interdependent Networked Game

PubMed Central

Jin, Qing; Wang, Lin; Xia, Cheng-Yi; Wang, Zhen

2014-01-01

Spatial evolution game has traditionally assumed that players interact with direct neighbors on a single network, which is isolated and not influenced by other systems. However, this is not fully consistent with recent research identification that interactions between networks play a crucial rule for the outcome of evolutionary games taking place on them. In this work, we introduce the simple game model into the interdependent networks composed of two networks. By means of imitation dynamics, we display that when the interdependent factor α is smaller than a threshold value αC, the symmetry of cooperation can be guaranteed. Interestingly, as interdependent factor exceeds αC, spontaneous symmetry breaking of fraction of cooperators presents itself between different networks. With respect to the breakage of symmetry, it is induced by asynchronous expansion between heterogeneous strategy couples of both networks, which further enriches the content of spatial reciprocity. Moreover, our results can be well predicted by the strategy-couple pair approximation method. PMID:24526076

Game Theoretical Analysis on Cooperation Stability and Incentive Effectiveness in Community Networks.

PubMed

Song, Kaida; Wang, Rui; Liu, Yi; Qian, Depei; Zhang, Han; Cai, Jihong

2015-01-01

Community networks, the distinguishing feature of which is membership admittance, appear on P2P networks, social networks, and conventional Web networks. Joining the network costs money, time or network bandwidth, but the individuals get access to special resources owned by the community in return. The prosperity and stability of the community are determined by both the policy of admittance and the attraction of the privileges gained by joining. However, some misbehaving users can get the dedicated resources with some illicit and low-cost approaches, which introduce instability into the community, a phenomenon that will destroy the membership policy. In this paper, we analyze on the stability using game theory on such a phenomenon. We propose a game-theoretical model of stability analysis in community networks and provide conditions for a stable community. We then extend the model to analyze the effectiveness of different incentive policies, which could be used when the community cannot maintain its members in certain situations. Then we verify those models through a simulation. Finally, we discuss several ways to promote community network's stability by adjusting the network's properties and give some proposal on the designs of these types of networks from the points of game theory and stability.

Game theory and extremal optimization for community detection in complex dynamic networks.

PubMed

Lung, Rodica Ioana; Chira, Camelia; Andreica, Anca

2014-01-01

The detection of evolving communities in dynamic complex networks is a challenging problem that recently received attention from the research community. Dynamics clearly add another complexity dimension to the difficult task of community detection. Methods should be able to detect changes in the network structure and produce a set of community structures corresponding to different timestamps and reflecting the evolution in time of network data. We propose a novel approach based on game theory elements and extremal optimization to address dynamic communities detection. Thus, the problem is formulated as a mathematical game in which nodes take the role of players that seek to choose a community that maximizes their profit viewed as a fitness function. Numerical results obtained for both synthetic and real-world networks illustrate the competitive performance of this game theoretical approach.

Navigable networks as Nash equilibria of navigation games

PubMed Central

Gulyás, András; Bíró, József J.; Kőrösi, Attila; Rétvári, Gábor; Krioukov, Dmitri

2015-01-01

Common sense suggests that networks are not random mazes of purposeless connections, but that these connections are organized so that networks can perform their functions well. One function common to many networks is targeted transport or navigation. Here, using game theory, we show that minimalistic networks designed to maximize the navigation efficiency at minimal cost share basic structural properties with real networks. These idealistic networks are Nash equilibria of a network construction game whose purpose is to find an optimal trade-off between the network cost and navigability. We show that these skeletons are present in the Internet, metabolic, English word, US airport, Hungarian road networks, and in a structural network of the human brain. The knowledge of these skeletons allows one to identify the minimal number of edges, by altering which one can efficiently improve or paralyse navigation in the network. PMID:26138277

Smartphone use and smartphone addiction in middle school students in Korea: Prevalence, social networking service, and game use.

PubMed

Cha, Seong-Soo; Seo, Bo-Kyung

2018-01-01

This study aimed to examine smartphone use patterns, smartphone addiction characteristics, and the predictive factors of the smartphone addiction in middle school students in South Korea. According to the Smartphone Addiction Proneness Scale scores, 563 (30.9%) were classified as a risk group for smartphone addiction and 1261 (69.1%) were identified as a normal user group. The adolescents used mobile messengers for the longest, followed by Internet surfing, gaming, and social networking service use. The two groups showed significant differences in smartphone use duration, awareness of game overuse, and purposes of playing games. The predictive factors of smartphone addiction were daily smartphone and social networking service use duration, and the awareness of game overuse.

Smartphone use and smartphone addiction in middle school students in Korea: Prevalence, social networking service, and game use

PubMed Central

Cha, Seong-Soo; Seo, Bo-Kyung

2018-01-01

This study aimed to examine smartphone use patterns, smartphone addiction characteristics, and the predictive factors of the smartphone addiction in middle school students in South Korea. According to the Smartphone Addiction Proneness Scale scores, 563 (30.9%) were classified as a risk group for smartphone addiction and 1261 (69.1%) were identified as a normal user group. The adolescents used mobile messengers for the longest, followed by Internet surfing, gaming, and social networking service use. The two groups showed significant differences in smartphone use duration, awareness of game overuse, and purposes of playing games. The predictive factors of smartphone addiction were daily smartphone and social networking service use duration, and the awareness of game overuse. PMID:29435355

A security mechanism based on evolutionary game in fog computing.

PubMed

Sun, Yan; Lin, Fuhong; Zhang, Nan

2018-02-01

Fog computing is a distributed computing paradigm at the edge of the network and requires cooperation of users and sharing of resources. When users in fog computing open their resources, their devices are easily intercepted and attacked because they are accessed through wireless network and present an extensive geographical distribution. In this study, a credible third party was introduced to supervise the behavior of users and protect the security of user cooperation. A fog computing security mechanism based on human nervous system is proposed, and the strategy for a stable system evolution is calculated. The MATLAB simulation results show that the proposed mechanism can reduce the number of attack behaviors effectively and stimulate users to cooperate in application tasks positively.

Study of network resource allocation based on market and game theoretic mechanism

NASA Astrophysics Data System (ADS)

Liu, Yingmei; Wang, Hongwei; Wang, Gang

2004-04-01

We work on the network resource allocation issue concerning network management system function based on market-oriented mechanism. The scheme is to model the telecommunication network resources as trading goods in which the various network components could be owned by different competitive, real-world entities. This is a multidisciplinary framework concentrating on the similarity between resource allocation in network environment and the market mechanism in economic theory. By taking an economic (market-based and game theoretic) approach in routing of communication network, we study the dynamic behavior under game-theoretic framework in allocating network resources. Based on the prior work of Gibney and Jennings, we apply concepts of utility and fitness to the market mechanism with an intention to close the gap between experiment environment and real world situation.

Dynamic phenomena and human activity in an artificial society

NASA Astrophysics Data System (ADS)

Grabowski, A.; Kruszewska, N.; Kosiński, R. A.

2008-12-01

We study dynamic phenomena in a large social network of nearly 3×104 individuals who interact in the large virtual world of a massive multiplayer online role playing game. On the basis of a database received from the online game server, we examine the structure of the friendship network and human dynamics. To investigate the relation between networks of acquaintances in virtual and real worlds, we carried out a survey among the players. We show that, even though the virtual network did not develop as a growing graph of an underlying network of social acquaintances in the real world, it influences it. Furthermore we find very interesting scaling laws concerning human dynamics. Our research shows how long people are interested in a single task and how much time they devote to it. Surprisingly, exponent values in both cases are close to -1 . We calculate the activity of individuals, i.e., the relative time daily devoted to interactions with others in the artificial society. Our research shows that the distribution of activity is not uniform and is highly correlated with the degree of the node, and that such human activity has a significant influence on dynamic phenomena, e.g., epidemic spreading and rumor propagation, in complex networks. We find that spreading is accelerated (an epidemic) or decelerated (a rumor) as a result of superspreaders’ various behavior.

On fairness, full cooperation, and quantum game with incomplete information

NASA Astrophysics Data System (ADS)

Lei, Zhen-Zhou; Liu, Bo-Yang; Yi, Ying; Dai, Hong-Yi; Zhang, Ming

2018-03-01

Quantum entanglement has emerged as a new resource to enhance cooperation and remove dilemmas. This paper aims to explore conditions under which full cooperation is achievable even when the information of payoff is incomplete. Based on the quantum version of the extended classical cash in a hat game, we demonstrate that quantum entanglement may be used for achieving full cooperation or avoiding moral hazards with the reasonable profit distribution policies even when the profit is uncertain to a certain degree. This research further suggests that the fairness of profit distribution should play an important role in promoting full cooperation. It is hopeful that quantum entanglement and fairness will promote full cooperation among distant people from various interest groups when quantum networks and quantum entanglement are accessible to the public. Project supported by the National Natural Science Foundation of China (Grant Nos. 61673389, 61273202, and 61134008.

Dilemma solving by the coevolution of networks and strategy in a 2 x 2 game.

PubMed

Tanimoto, Jun

2007-08-01

A 2 x 2 game model implemented by a coevolution mechanism of both networks and strategy, inspired by the work of Zimmermann and Eguiluz [Phys. Rev. E72, 056118 (2005)] is established. Network adaptation is the manner in which an existing link between two agents is destroyed and how a new one is established to replace it. The strategy is defined as whether an agent offers cooperation (C) or defection (D) . Both the networks and strategy are synchronously renovated in a simulation time step. A series of numerical experiments, considering various 2 x 2 game structures, reveals that the proposed coevolution mechanism can solve dilemmas in several game classes. The effect of solving a dilemma means mutual-cooperation reciprocity (R reciprocity), which is brought about by emerging several cooperative hub agents who have plenty of links. This effect can be primarily observed in game classes of the prisoner's dilemma and stag hunt. The coevolution mechanism, however, seems counterproductive for game classes of leader and hero, where the alternating reciprocity (ST reciprocity) is meaningful.

Game among interdependent networks: The impact of rationality on system robustness

NASA Astrophysics Data System (ADS)

Fan, Yuhang; Cao, Gongze; He, Shibo; Chen, Jiming; Sun, Youxian

2016-12-01

Many real-world systems are composed of interdependent networks that rely on one another. Such networks are typically designed and operated by different entities, who aim at maximizing their own payoffs. There exists a game among these entities when designing their own networks. In this paper, we study the game investigating how the rational behaviors of entities impact the system robustness. We first introduce a mathematical model to quantify the interacting payoffs among varying entities. Then we study the Nash equilibrium of the game and compare it with the optimal social welfare. We reveal that the cooperation among different entities can be reached to maximize the social welfare in continuous game only when the average degree of each network is constant. Therefore, the huge gap between Nash equilibrium and optimal social welfare generally exists. The rationality of entities makes the system inherently deficient and even renders it extremely vulnerable in some cases. We analyze our model for two concrete systems with continuous strategy space and discrete strategy space, respectively. Furthermore, we uncover some factors (such as weakening coupled strength of interdependent networks, designing a suitable topology dependence of the system) that help reduce the gap and the system vulnerability.

Economic Feasibility of Wireless Sensor Network-Based Service Provision in a Duopoly Setting with a Monopolist Operator.

PubMed

Sanchis-Cano, Angel; Romero, Julián; Sacoto-Cabrera, Erwin J; Guijarro, Luis

2017-11-25

We analyze the feasibility of providing Wireless Sensor Network-data-based services in an Internet of Things scenario from an economical point of view. The scenario has two competing service providers with their own private sensor networks, a network operator and final users. The scenario is analyzed as two games using game theory. In the first game, sensors decide to subscribe or not to the network operator to upload the collected sensing-data, based on a utility function related to the mean service time and the price charged by the operator. In the second game, users decide to subscribe or not to the sensor-data-based service of the service providers based on a Logit discrete choice model related to the quality of the data collected and the subscription price. The sinks and users subscription stages are analyzed using population games and discrete choice models, while network operator and service providers pricing stages are analyzed using optimization and Nash equilibrium concepts respectively. The model is shown feasible from an economic point of view for all the actors if there are enough interested final users and opens the possibility of developing more efficient models with different types of services.

Effects of adaptive degrees of trust on coevolution of quantum strategies on scale-free networks.

PubMed

Li, Qiang; Chen, Minyou; Perc, Matjaž; Iqbal, Azhar; Abbott, Derek

2013-10-15

We study the impact of adaptive degrees of trust on the evolution of cooperation in the quantum prisoner's dilemma game. In addition to the strategies, links between players are also subject to evolution. Starting with a scale-free interaction network, players adjust trust towards their neighbors based on received payoffs. The latter governs the strategy adoption process, while trust governs the rewiring of links. As soon as the degree of trust towards a neighbor drops to zero, the link is rewired to another randomly chosen player within the network. We find that for small temptations to defect cooperators always dominate, while for intermediate and strong temptations a single quantum strategy is able to outperform all other strategies. In general, reciprocal trust remains within close relationships and favors the dominance of a single strategy. Due to coevolution, the power-law degree distributions transform to Poisson distributions.

Effects of adaptive degrees of trust on coevolution of quantum strategies on scale-free networks

NASA Astrophysics Data System (ADS)

Li, Qiang; Chen, Minyou; Perc, Matjaž; Iqbal, Azhar; Abbott, Derek

2013-10-01

We study the impact of adaptive degrees of trust on the evolution of cooperation in the quantum prisoner's dilemma game. In addition to the strategies, links between players are also subject to evolution. Starting with a scale-free interaction network, players adjust trust towards their neighbors based on received payoffs. The latter governs the strategy adoption process, while trust governs the rewiring of links. As soon as the degree of trust towards a neighbor drops to zero, the link is rewired to another randomly chosen player within the network. We find that for small temptations to defect cooperators always dominate, while for intermediate and strong temptations a single quantum strategy is able to outperform all other strategies. In general, reciprocal trust remains within close relationships and favors the dominance of a single strategy. Due to coevolution, the power-law degree distributions transform to Poisson distributions.

Importance of tie strengths in the prisoner's dilemma game on social networks

NASA Astrophysics Data System (ADS)

Xu, Bo; Liu, Lu; You, Weijia

2011-06-01

Though numerous researches have shown that tie strengths play a key role in the formation of collective behavior in social networks, little work has been done to explore their impact on the outcome of evolutionary games. In this Letter, we studied the effect of tie strength in the dynamics of evolutionary prisoner's dilemma games by using online social network datasets. The results show that the fraction of cooperators has a non-trivial dependence on tie strength. Weak ties, just like previous researches on epidemics and information diffusion have shown, play a key role by the maintenance of cooperators in evolutionary prisoner's dilemma games.

Entanglement guarantees emergence of cooperation in quantum prisoner's dilemma games on networks.

PubMed

Li, Angsheng; Yong, Xi

2014-09-05

It was known that cooperation of evolutionary prisoner's dilemma games fails to emerge in homogenous networks such as random graphs. Here we proposed a quantum prisoner's dilemma game. The game consists of two players, in which each player has three choices of strategy: cooperator (C), defector (D) and super cooperator (denoted by Q). We found that quantum entanglement guarantees emergence of a new cooperation, the super cooperation of the quantum prisoner's dilemma games, and that entanglement is the mechanism of guaranteed emergence of cooperation of evolutionary prisoner's dilemma games on networks. We showed that for a game with temptation b, there exists a threshold arccos √b/b for a measurement of entanglement, beyond which, (super) cooperation of evolutionary quantum prisoner's dilemma games is guaranteed to quickly emerge, giving rise to stochastic convergence of the cooperations, that if the entanglement degree γ is less than the threshold arccos √b/b, then the equilibrium frequency of cooperations of the games is positively correlated to the entanglement degree γ, and that if γ is less than arccos √b/b and b is beyond some boundary, then the equilibrium frequency of cooperations of the games on random graphs decreases as the average degree of the graphs increases.

Reciprocity in spatial evolutionary public goods game on double-layered network

NASA Astrophysics Data System (ADS)

Kim, Jinho; Yook, Soon-Hyung; Kim, Yup

2016-08-01

Spatial evolutionary games have mainly been studied on a single, isolated network. However, in real world systems, many interaction topologies are not isolated but many different types of networks are inter-connected to each other. In this study, we investigate the spatial evolutionary public goods game (SEPGG) on double-layered random networks (DRN). Based on the mean-field type arguments and numerical simulations, we find that SEPGG on DRN shows very rich interesting phenomena, especially, depending on the size of each layer, intra-connectivity, and inter-connected couplings, the network reciprocity of SEPGG on DRN can be drastically enhanced through the inter-connected coupling. Furthermore, SEPGG on DRN can provide a more general framework which includes the evolutionary dynamics on multiplex networks and inter-connected networks at the same time.

Reciprocity in spatial evolutionary public goods game on double-layered network

PubMed Central

Kim, Jinho; Yook, Soon-Hyung; Kim, Yup

2016-01-01

Spatial evolutionary games have mainly been studied on a single, isolated network. However, in real world systems, many interaction topologies are not isolated but many different types of networks are inter-connected to each other. In this study, we investigate the spatial evolutionary public goods game (SEPGG) on double-layered random networks (DRN). Based on the mean-field type arguments and numerical simulations, we find that SEPGG on DRN shows very rich interesting phenomena, especially, depending on the size of each layer, intra-connectivity, and inter-connected couplings, the network reciprocity of SEPGG on DRN can be drastically enhanced through the inter-connected coupling. Furthermore, SEPGG on DRN can provide a more general framework which includes the evolutionary dynamics on multiplex networks and inter-connected networks at the same time. PMID:27503801

Naming Game on Networks: Let Everyone be Both Speaker and Hearer

PubMed Central

Gao, Yuan; Chen, Guanrong; Chan, Rosa H. M.

2014-01-01

To investigate how consensus is reached on a large self-organized peer-to-peer network, we extended the naming game model commonly used in language and communication to Naming Game in Groups (NGG). Differing from other existing naming game models, in NGG everyone in the population (network) can be both speaker and hearer simultaneously, which resembles in a closer manner to real-life scenarios. Moreover, NGG allows the transmission (communication) of multiple words (opinions) for multiple intra-group consensuses. The communications among indirectly-connected nodes are also enabled in NGG. We simulated and analyzed the consensus process in some typical network topologies, including random-graph networks, small-world networks and scale-free networks, to better understand how global convergence (consensus) could be reached on one common word. The results are interpreted on group negotiation of a peer-to-peer network, which shows that global consensus in the population can be reached more rapidly when more opinions are permitted within each group or when the negotiating groups in the population are larger in size. The novel features and properties introduced by our model have demonstrated its applicability in better investigating general consensus problems on peer-to-peer networks. PMID:25143140

Naming Game on Networks: Let Everyone be Both Speaker and Hearer

NASA Astrophysics Data System (ADS)

Gao, Yuan; Chen, Guanrong; Chan, Rosa H. M.

2014-08-01

To investigate how consensus is reached on a large self-organized peer-to-peer network, we extended the naming game model commonly used in language and communication to Naming Game in Groups (NGG). Differing from other existing naming game models, in NGG everyone in the population (network) can be both speaker and hearer simultaneously, which resembles in a closer manner to real-life scenarios. Moreover, NGG allows the transmission (communication) of multiple words (opinions) for multiple intra-group consensuses. The communications among indirectly-connected nodes are also enabled in NGG. We simulated and analyzed the consensus process in some typical network topologies, including random-graph networks, small-world networks and scale-free networks, to better understand how global convergence (consensus) could be reached on one common word. The results are interpreted on group negotiation of a peer-to-peer network, which shows that global consensus in the population can be reached more rapidly when more opinions are permitted within each group or when the negotiating groups in the population are larger in size. The novel features and properties introduced by our model have demonstrated its applicability in better investigating general consensus problems on peer-to-peer networks.

An Energy-Efficient Game-Theory-Based Spectrum Decision Scheme for Cognitive Radio Sensor Networks

PubMed Central

Salim, Shelly; Moh, Sangman

2016-01-01

A cognitive radio sensor network (CRSN) is a wireless sensor network in which sensor nodes are equipped with cognitive radio. In this paper, we propose an energy-efficient game-theory-based spectrum decision (EGSD) scheme for CRSNs to prolong the network lifetime. Note that energy efficiency is the most important design consideration in CRSNs because it determines the network lifetime. The central part of the EGSD scheme consists of two spectrum selection algorithms: random selection and game-theory-based selection. The EGSD scheme also includes a clustering algorithm, spectrum characterization with a Markov chain, and cluster member coordination. Our performance study shows that EGSD outperforms the existing popular framework in terms of network lifetime and coordination overhead. PMID:27376290

An Energy-Efficient Game-Theory-Based Spectrum Decision Scheme for Cognitive Radio Sensor Networks.

PubMed

Salim, Shelly; Moh, Sangman

2016-06-30

A cognitive radio sensor network (CRSN) is a wireless sensor network in which sensor nodes are equipped with cognitive radio. In this paper, we propose an energy-efficient game-theory-based spectrum decision (EGSD) scheme for CRSNs to prolong the network lifetime. Note that energy efficiency is the most important design consideration in CRSNs because it determines the network lifetime. The central part of the EGSD scheme consists of two spectrum selection algorithms: random selection and game-theory-based selection. The EGSD scheme also includes a clustering algorithm, spectrum characterization with a Markov chain, and cluster member coordination. Our performance study shows that EGSD outperforms the existing popular framework in terms of network lifetime and coordination overhead.

Learning and coordinating in a multilayer network

PubMed Central

Lugo, Haydée; Miguel, Maxi San

2015-01-01

We introduce a two layer network model for social coordination incorporating two relevant ingredients: a) different networks of interaction to learn and to obtain a pay-off, and b) decision making processes based both on social and strategic motivations. Two populations of agents are distributed in two layers with intralayer learning processes and playing interlayer a coordination game. We find that the skepticism about the wisdom of crowd and the local connectivity are the driving forces to accomplish full coordination of the two populations, while polarized coordinated layers are only possible for all-to-all interactions. Local interactions also allow for full coordination in the socially efficient Pareto-dominant strategy in spite of being the riskier one. PMID:25585934

Game Theory Meets Wireless Sensor Networks Security Requirements and Threats Mitigation: A Survey.

PubMed

Abdalzaher, Mohamed S; Seddik, Karim; Elsabrouty, Maha; Muta, Osamu; Furukawa, Hiroshi; Abdel-Rahman, Adel

2016-06-29

We present a study of using game theory for protecting wireless sensor networks (WSNs) from selfish behavior or malicious nodes. Due to scalability, low complexity and disseminated nature of WSNs, malicious attacks can be modeled effectively using game theory. In this study, we survey the different game-theoretic defense strategies for WSNs. We present a taxonomy of the game theory approaches based on the nature of the attack, whether it is caused by an external attacker or it is the result of an internal node acting selfishly or maliciously. We also present a general trust model using game theory for decision making. We, finally, identify the significant role of evolutionary games for WSNs security against intelligent attacks; then, we list several prospect applications of game theory to enhance the data trustworthiness and node cooperation in different WSNs.

The influence of tie strength on evolutionary games on networks: An empirical investigation

NASA Astrophysics Data System (ADS)

Buesser, Pierre; Peña, Jorge; Pestelacci, Enea; Tomassini, Marco

2011-11-01

Extending previous work on unweighted networks, we present here a systematic numerical investigation of standard evolutionary games on weighted networks. In the absence of any reliable model for generating weighted social networks, we attribute weights to links in a few ways supported by empirical data ranging from totally uncorrelated to weighted bipartite networks. The results of the extensive simulation work on standard complex network models show that, except in a case that does not seem to be common in social networks, taking the tie strength into account does not change in a radical manner the long-run steady-state behavior of the studied games. Besides model networks, we also included a real-life case drawn from a coauthorship network. In this case also, taking the weights into account only changes the results slightly with respect to the raw unweighted graph, although to draw more reliable conclusions on real social networks many more cases should be studied as these weighted networks become available.

Economic Feasibility of Wireless Sensor Network-Based Service Provision in a Duopoly Setting with a Monopolist Operator

PubMed Central

Romero, Julián; Sacoto-Cabrera, Erwin J.

2017-01-01

We analyze the feasibility of providing Wireless Sensor Network-data-based services in an Internet of Things scenario from an economical point of view. The scenario has two competing service providers with their own private sensor networks, a network operator and final users. The scenario is analyzed as two games using game theory. In the first game, sensors decide to subscribe or not to the network operator to upload the collected sensing-data, based on a utility function related to the mean service time and the price charged by the operator. In the second game, users decide to subscribe or not to the sensor-data-based service of the service providers based on a Logit discrete choice model related to the quality of the data collected and the subscription price. The sinks and users subscription stages are analyzed using population games and discrete choice models, while network operator and service providers pricing stages are analyzed using optimization and Nash equilibrium concepts respectively. The model is shown feasible from an economic point of view for all the actors if there are enough interested final users and opens the possibility of developing more efficient models with different types of services. PMID:29186847

Dynamic Power Distribution System Management With a Locally Connected Communication Network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dall-Anese, Emiliano; Zhang, Kaiqing; Basar, Tamer

Coordinated optimization and control of distribution-level assets can enable a reliable and optimal integration of massive amount of distributed energy resources (DERs) and facilitate distribution system management (DSM). Accordingly, the objective is to coordinate the power injection at the DERs to maintain certain quantities across the network, e.g., voltage magnitude, line flows, or line losses, to be close to a desired profile. By and large, the performance of the DSM algorithms has been challenged by two factors: i) the possibly non-strongly connected communication network over DERs that hinders the coordination; ii) the dynamics of the real system caused by themore » DERs with heterogeneous capabilities, time-varying operating conditions, and real-time measurement mismatches. In this paper, we investigate the modeling and algorithm design and analysis with the consideration of these two factors. In particular, a game theoretic characterization is first proposed to account for a locally connected communication network over DERs, along with the analysis of the existence and uniqueness of the Nash equilibrium (NE) therein. To achieve the equilibrium in a distributed fashion, a projected-gradient-based asynchronous DSM algorithm is then advocated. The algorithm performance, including the convergence speed and the tracking error, is analytically guaranteed under the dynamic setting. Extensive numerical tests on both synthetic and realistic cases corroborate the analytical results derived.« less

Chaotic evolution of prisoner's dilemma game with volunteering on interdependent networks

NASA Astrophysics Data System (ADS)

Luo, Chao; Zhang, Xiaolin; Zheng, YuanJie

2017-06-01

In this article, the evolution of prisoner's dilemma game with volunteering on interdependent networks is investigated. Different from the traditional two-strategy game, voluntary participation as an additional strategy is involved in repeated game, that can introduce more complex evolutionary dynamics. And, interdependent networks provide a more generalized network architecture to study the intricate variability of dynamics. We have showed that voluntary participation could effectively promote the density of co-operation, that is also greatly affected by interdependent strength between two coupled networks. We further discussed the influence of interdependent strength on the densities of different strategies and found that an intermediate interdependence would play a bigger role on the evolution of dynamics. Subsequently, the critical values of the defection temptation for phase transitions under different conditions have been studied. Moreover, the global oscillations induced by the circle of dominance of three strategies on interdependent networks have been quantitatively investigated. Counter-intuitively, the oscillations of strategy densities are not periodic or stochastic, but have rich dynamical behaviors. By means of various analysis tools, we have demonstrated the global oscillations of strategy densities possessed chaotic characteristics.

A Dynamic Game on Network Topology for Counterinsurgency Applications

DTIC Science & Technology

2015-03-26

scenario. This study creates a dynamic game on network topology to provide insight into the effec- tiveness of offensive targeting strategies determined by...focused upon the diffusion of thoughts and innovations throughout complex social networks. Coleman et al. (1966) and Ryan & Gross (1950) investigated...free networks make them extremely resilient against errors but very vulnerable to attack. Most interest- ingly, a determined attacker can remove well

Using Game Theoretic Models to Predict Pilot Behavior in NextGen Merging and Landing Scenario

NASA Technical Reports Server (NTRS)

Yildiz, Yildiray; Lee, Ritchie; Brat, Guillaume

2012-01-01

In this paper, we present an implementation of the Semi Network-Form Game framework to predict pilot behavior in a merging and landing scenario. In this scenario, two aircraft are approaching to a freeze horizon with approximately equal distance when they become aware of each other via an ADS-B communication link that will be available in NextGen airspace. Both pilots want to gain advantage over the other by entering the freeze horizon earlier and obtain the first place in landing. They re-adjust their speed accordingly. However, they cannot simply increase their speed to the maximum allowable values since they are concerned with safety, separation distance, effort, possibility of being vectored-off from landing and possibility of violating speed constraints. We present how to model these concerns and the rest of the system using semi network-from game framework. Using this framework, based on certain assumptions on pilot utility functions and on system configuration, we provide estimates of pilot behavior and overall system evolution in time. We also discuss the possible employment of this modeling tool for airspace design optimization. To support this discussion, we provide a case where we investigate the effect of increasing the merging point speed limit on the commanded speed distribution and on the percentage of vectored aircraft.

Game Theory Meets Wireless Sensor Networks Security Requirements and Threats Mitigation: A Survey

PubMed Central

Abdalzaher, Mohamed S.; Seddik, Karim; Elsabrouty, Maha; Muta, Osamu; Furukawa, Hiroshi; Abdel-Rahman, Adel

2016-01-01

We present a study of using game theory for protecting wireless sensor networks (WSNs) from selfish behavior or malicious nodes. Due to scalability, low complexity and disseminated nature of WSNs, malicious attacks can be modeled effectively using game theory. In this study, we survey the different game-theoretic defense strategies for WSNs. We present a taxonomy of the game theory approaches based on the nature of the attack, whether it is caused by an external attacker or it is the result of an internal node acting selfishly or maliciously. We also present a general trust model using game theory for decision making. We, finally, identify the significant role of evolutionary games for WSNs security against intelligent attacks; then, we list several prospect applications of game theory to enhance the data trustworthiness and node cooperation in different WSNs. PMID:27367700

Efficient Algorithmic Frameworks via Structural Graph Theory

DTIC Science & Technology

2016-10-28

centrally planned solution. Policy recommendation: Given a socioeconomic game among multiple parties (countries, armies, political parties, terrorist...etc.). 2 Graph Structure of Network Creation Games We completed the final versions of two of our papers about the graph structure inherent in...network creation games ”, which appeared in the following venues: Erik D. Demaine, MohammadTaghi Hajiaghayi, Hamid Mahini, and Morteza Zadi- moghaddam, “The

Applying graphs and complex networks to football metric interpretation.

PubMed

Arriaza-Ardiles, E; Martín-González, J M; Zuniga, M D; Sánchez-Flores, J; de Saa, Y; García-Manso, J M

2018-02-01

This work presents a methodology for analysing the interactions between players in a football team, from the point of view of graph theory and complex networks. We model the complex network of passing interactions between players of a same team in 32 official matches of the Liga de Fútbol Profesional (Spain), using a passing/reception graph. This methodology allows us to understand the play structure of the team, by analysing the offensive phases of game-play. We utilise two different strategies for characterising the contribution of the players to the team: the clustering coefficient, and centrality metrics (closeness and betweenness). We show the application of this methodology by analyzing the performance of a professional Spanish team according to these metrics and the distribution of passing/reception in the field. Keeping in mind the dynamic nature of collective sports, in the future we will incorporate metrics which allows us to analyse the performance of the team also according to the circumstances of game-play and to different contextual variables such as, the utilisation of the field space, the time, and the ball, according to specific tactical situations. Copyright © 2017 Elsevier B.V. All rights reserved.

Citizen seismology in Taiwan: what went wrong and what is the future?

NASA Astrophysics Data System (ADS)

Chen, K. H.; Liang, W. T.; Wu, Y. F.

2017-12-01

Citizen seismology encourages the public involvement to data collection, analysis, and reporting, and has the potential to greatly improve the emergency response to seismic hazard. This of course, is important for scientific achievement due to the dense network. We believed the value of citizen seismology and started with distributing Quake-Catcher-Network (QCN) sensor at schools in Taiwan. While working with teachers, we hoped to motivate the learning of how to read seismograms, what to see in the data, and what to teach in the class. Through lots of workshops and activities, even with near-real time earthquake game competition and board game (quake-nopoly) developed along the way, we came to realize the huge gap between what people need and what we do. And to bridge the gap, a new generation of citizen seismic network is needed. Imagine at work, you receive the alarm from sensors at home that tells you the location, size, and type of anomalous shaking events in the neighborhood. Can this future "warning" system happen, allowing citizen to do emergence response? This is a story about facing the challenge, transforming the doubt of "why do I care" to a future IoT world.

Hack-proof Synchronization Protocol for Multi-player Online Games

NASA Astrophysics Data System (ADS)

Fung, Yeung Siu; Lui, John C. S.

Modern multi-player online games are popular and attractive because they provide a sense of virtual world experience to users: players can interact with each other on the Internet but perceive a local area network responsiveness. To make this possible, most modern multi-player online games use similar networking architecture that aims to hide the effects of network latency, packet loss, and high variance of delay from players. Because real-time interactivity is a crucial feature from a player's point of view, any delay perceived by a player can affect his/her performance [16]. Therefore, the game client must be able to run and accept new user commands continuously regardless of the condition of the underlying communication channel, and that it will not stop responding because of waiting for update packets from other players. To make this possible, multi-player online games typically use protocols based on "dead-reckoning" [5, 6, 9] which allows loose synchronization between players.

Ethernet access network based on free-space optic deployment technology

NASA Astrophysics Data System (ADS)

Gebhart, Michael; Leitgeb, Erich; Birnbacher, Ulla; Schrotter, Peter

2004-06-01

The satisfaction of all communication needs from single households and business companies over a single access infrastructure is probably the most challenging topic in communications technology today. But even though the so-called "Last Mile Access Bottleneck" is well known since more than ten years and many distribution technologies have been tried out, the optimal solution has not yet been found and paying commercial access networks offering all service classes are still rare today. Conventional services like telephone, radio and TV, as well as new and emerging services like email, web browsing, online-gaming, video conferences, business data transfer or external data storage can all be transmitted over the well known and cost effective Ethernet networking protocol standard. Key requirements for the deployment technology driven by the different services are high data rates to the single customer, security, moderate deployment costs and good scalability to number and density of users, quick and flexible deployment without legal impediments and high availability, referring to the properties of optical and wireless communication. We demonstrate all elements of an Ethernet Access Network based on Free Space Optic distribution technology. Main physical parts are Central Office, Distribution Network and Customer Equipment. Transmission of different services, as well as configuration, service upgrades and remote control of the network are handled by networking features over one FSO connection. All parts of the network are proven, the latest commercially available technology. The set up is flexible and can be adapted to any more specific need if required.

Evaluation of a Web-based social network electronic game in enhancing mental health literacy for young people.

PubMed

Li, Tim M H; Chau, Michael; Wong, Paul W C; Lai, Eliza S Y; Yip, Paul S F

2013-05-15

Internet-based learning programs provide people with massive health care information and self-help guidelines on improving their health. The advent of Web 2.0 and social networks renders significant flexibility to embedding highly interactive components, such as games, to foster learning processes. The effectiveness of game-based learning on social networks has not yet been fully evaluated. The aim of this study was to assess the effectiveness of a fully automated, Web-based, social network electronic game on enhancing mental health knowledge and problem-solving skills of young people. We investigated potential motivational constructs directly affecting the learning outcome. Gender differences in learning outcome and motivation were also examined. A pre/posttest design was used to evaluate the fully automated Web-based intervention. Participants, recruited from a closed online user group, self-assessed their mental health literacy and motivational constructs before and after completing the game within a 3-week period. The electronic game was designed according to cognitive-behavioral approaches. Completers and intent-to-treat analyses, using multiple imputation for missing data, were performed. Regression analysis with backward selection was employed when examining the relationship between knowledge enhancement and motivational constructs. The sample included 73 undergraduates (42 females) for completers analysis. The gaming approach was effective in enhancing young people's mental health literacy (d=0.65). The finding was also consistent with the intent-to-treat analysis, which included 127 undergraduates (75 females). No gender differences were found in learning outcome (P=.97). Intrinsic goal orientation was the primary factor in learning motivation, whereas test anxiety was successfully alleviated in the game setting. No gender differences were found on any learning motivation subscales (P>.10). We also found that participants' self-efficacy for learning and performance, as well as test anxiety, significantly affected their learning outcomes, whereas other motivational subscales were statistically nonsignificant. Electronic games implemented through social networking sites appear to effectively enhance users' mental health literacy.

Having mentors and campus social networks moderates the impact of worries and video gaming on depressive symptoms: a moderated mediation analysis.

PubMed

Lee, Jong-Sun; Jeong, Bumseok

2014-05-05

Easy access to the internet has spawned a wealth of research to investigate the effects of its use on depression. However, one limitation of many previous studies is that they disregard the interactive mechanisms of risk and protective factors. The aim of the present study was to investigate a resilience model in the relationship between worry, daily internet video game playing, daily sleep duration, mentors, social networks and depression, using a moderated mediation analysis. 6068 Korean undergraduate and graduate students participated in this study. The participants completed a web-based mental health screening questionnaire including the Beck Depression Inventory (BDI) and information about number of worries, number of mentors, number of campus social networks, daily sleep duration, daily amount of internet video game playing and daily amount of internet searching on computer or smartphone. A moderated mediation analysis was carried out using the PROCESS macro which allowed the inclusion of mediators and moderator in the same model. The results showed that the daily amount of internet video game playing and daily sleep duration partially mediated the association between the number of worries and the severity of depression. In addition, the mediating effect of the daily amount of internet video game playing was moderated by both the number of mentors and the number of campus social networks. The current findings indicate that the negative impact of worry on depression through internet video game playing can be buffered when students seek to have a number of mentors and campus social networks. Interventions should therefore target individuals who have higher number of worries but seek only a few mentors or campus social networks. Social support via campus mentorship and social networks ameliorate the severity of depression in university students.

Cooperation among cancer cells as public goods games on Voronoi networks.

PubMed

Archetti, Marco

2016-05-07

Cancer cells produce growth factors that diffuse and sustain tumour proliferation, a form of cooperation that can be studied using mathematical models of public goods in the framework of evolutionary game theory. Cell populations, however, form heterogeneous networks that cannot be described by regular lattices or scale-free networks, the types of graphs generally used in the study of cooperation. To describe the dynamics of growth factor production in populations of cancer cells, I study public goods games on Voronoi networks, using a range of non-linear benefits that account for the known properties of growth factors, and different types of diffusion gradients. The results are surprisingly similar to those obtained on regular graphs and different from results on scale-free networks, revealing that network heterogeneity per se does not promote cooperation when public goods diffuse beyond one-step neighbours. The exact shape of the diffusion gradient is not crucial, however, whereas the type of non-linear benefit is an essential determinant of the dynamics. Public goods games on Voronoi networks can shed light on intra-tumour heterogeneity, the evolution of resistance to therapies that target growth factors, and new types of cell therapy. Copyright © 2016 Elsevier Ltd. All rights reserved.

Group Formation in Economics

NASA Astrophysics Data System (ADS)

Demange, Gabrielle; Wooders, Myrna

2005-01-01

Broad and diverse ranges of activities are conducted within and by organized groups of individuals, including political, economic and social activities. These activities have recently become a subject of intense interest in economics and game theory. Some of the topics investigated in this collection are models of networks of power and privilege, trade networks, co-authorship networks, buyer-seller networks with differentiated products, and networks of medical innovation and the adaptation of new information. Other topics are social norms on punctuality, clubs and the provision of club goods and public goods, research and development and collusive alliances among corporations, and international alliances and trading agreements. While relatively recent, the literature on game theoretic studies of group formation in economics is already vast. This volume provides an introduction to this important literature on game-theoretic treatments of situations with networks, clubs, and coalitions, including some applications.

A game theory-based trust measurement model for social networks.

PubMed

Wang, Yingjie; Cai, Zhipeng; Yin, Guisheng; Gao, Yang; Tong, Xiangrong; Han, Qilong

2016-01-01

In social networks, trust is a complex social network. Participants in online social networks want to share information and experiences with as many reliable users as possible. However, the modeling of trust is complicated and application dependent. Modeling trust needs to consider interaction history, recommendation, user behaviors and so on. Therefore, modeling trust is an important focus for online social networks. We propose a game theory-based trust measurement model for social networks. The trust degree is calculated from three aspects, service reliability, feedback effectiveness, recommendation credibility, to get more accurate result. In addition, to alleviate the free-riding problem, we propose a game theory-based punishment mechanism for specific trust and global trust, respectively. We prove that the proposed trust measurement model is effective. The free-riding problem can be resolved effectively through adding the proposed punishment mechanism.

Effective seeding strategy in evolutionary prisoner's dilemma games on online social networks

NASA Astrophysics Data System (ADS)

Xu, Bo; Shi, Huibin; Wang, Jianwei; Huang, Yun

2015-04-01

This paper explores effective seeding strategies in prisoner's dilemma game (PDG) on online social networks, i.e. the optimal strategy to obtain global cooperation with minimum cost. Three distinct seeding strategies are compared by performing computer simulations on real online social network datasets. Our finding suggests that degree centrality seeding outperforms other strategies regardless of the initial payoff setting or network size. Celebrities of online social networks play key roles in preserving cooperation.

Cooperation in the prisoner's dilemma game on tunable community networks

NASA Astrophysics Data System (ADS)

Liu, Penghui; Liu, Jing

2017-04-01

Community networks have attracted lots of attention as they widely exist in the real world and are essential to study properties of networks. As the game theory illustrates the competitive relationship among individuals, studying the iterated prisoner's dilemma games (PDG) on community networks is meaningful. In this paper, we focus on investigating the relationship between the cooperation level of community networks and that of their communities in the prisoner's dilemma games. With this purpose in mind, a type of tunable community networks whose communities inherit not only the scale-free property, but also the characteristic of adjustable cooperation level of Holme and Kim (HK) networks is designed. Both uniform and non-uniform community networks are investigated. We find out that cooperation enhancement of communities can improve the cooperation level of the whole networks. Moreover, simulation results indicate that a large community is a better choice than a small community to improve the cooperation level of the whole networks. Thus, improving the cooperation level of community networks can be divided into a number of sub-problems targeting at improving the cooperation level of individual communities, which can save the computation cost and deal with the problem of improving the cooperation level of huge community networks. Moreover, as the larger community is a better choice, it is reasonable to start with large communities, according to the greedy strategy when the number of nodes can participate in the enhancement is limited.

Game Theoretic Models of Competition and Upgrade Investments in Communication Networks

ERIC Educational Resources Information Center

Wu, Shuang

2010-01-01

In the first part of this dissertation, we study the competition among network service providers in a parallel-link network with the presence of elastic user demand that diminishes both with higher prices and congestion. First we analyze a game where providers strategically price their service for single class of traffic. Later we analyze a game…

Identifying Key Actors in Heterogeneous Networks

DTIC Science & Technology

2017-11-29

analysis (SNA) and game theory (GT) to improve accuracy for detecting significant or “powerful” actors within a total actor space when both resource...coalesce in order to achieve a desired outcome. Cooperative game theory (CGT) models of coalition formation are based on two limiting assumptions: that...demonstration of a new approach for synthesizing social network analysis and game theory. The ultimate goal of this research agenda is to generalize

Who Networks? The Social Psychology of Virtual Communities

DTIC Science & Technology

2004-06-01

virtual life: the open side - characterized by communities of interest, civil society movements, virtual “states,” and 4 online gaming communities...network of people hailing from Sicily. Sometimes the offline/ online similari- ties mesh even more, as when a gaming society in a small Swedish town...Commercially owned and regulated graphics-based Massively Multi- Player Gaming Communities (EverQuest, The Matrix Online ®, etc.) • UseNET

Effects of adaptive dynamical linking in networked games

NASA Astrophysics Data System (ADS)

Yang, Zhihu; Li, Zhi; Wu, Te; Wang, Long

2013-10-01

The role of dynamical topologies in the evolution of cooperation has received considerable attention, as some studies have demonstrated that dynamical networks are much better than static networks in terms of boosting cooperation. Here we study a dynamical model of evolution of cooperation on stochastic dynamical networks in which there are no permanent partners to each agent. Whenever a new link is created, its duration is randomly assigned without any bias or preference. We allow the agent to adaptively adjust the duration of each link during the evolution in accordance with the feedback from game interactions. By Monte Carlo simulations, we find that cooperation can be remarkably promoted by this adaptive dynamical linking mechanism both for the game of pairwise interactions, such as the Prisoner's Dilemma game (PDG), and for the game of group interactions, illustrated by the public goods game (PGG). And the faster the adjusting rate, the more successful the evolution of cooperation. We also show that in this context weak selection favors cooperation much more than strong selection does. What is particularly meaningful is that the prosperity of cooperation in this study indicates that the rationality and selfishness of a single agent in adjusting social ties can lead to the progress of altruism of the whole population.

Supercooperation in evolutionary games on correlated weighted networks.

PubMed

Buesser, Pierre; Tomassini, Marco

2012-01-01

In this work we study the behavior of classical two-person, two-strategies evolutionary games on a class of weighted networks derived from Barabási-Albert and random scale-free unweighted graphs. Using customary imitative dynamics, our numerical simulation results show that the presence of link weights that are correlated in a particular manner with the degree of the link end points leads to unprecedented levels of cooperation in the whole games' phase space, well above those found for the corresponding unweighted complex networks. We provide intuitive explanations for this favorable behavior by transforming the weighted networks into unweighted ones with particular topological properties. The resulting structures help us to understand why cooperation can thrive and also give ideas as to how such supercooperative networks might be built.

Game-theoretic cooperativity in networks of self-interested units

NASA Astrophysics Data System (ADS)

Barto, Andrew G.

1986-08-01

The behavior of theoretical neural networks is often described in terms of competition and cooperation. I present an approach to network learning that is related to game and team problems in which competition and cooperation have more technical meanings. I briefly describe the application of stochastic learning automata to game and team problems and then present an adaptive element that is a synthesis of aspects of stochastic learning automata and typical neuron-like adaptive elements. These elements act as self-interested agents that work toward improving their performance with respect to their individual preference orderings. Networks of these elements can solve a variety of team decision problems, some of which take the form of layered networks in which the ``hidden units'' become appropriate functional components as they attempt to improve their own payoffs.

Coalition Formation and Spectrum Sharing of Cooperative Spectrum Sensing Participants.

PubMed

Zhensheng Jiang; Wei Yuan; Leung, Henry; Xinge You; Qi Zheng

2017-05-01

In cognitive radio networks, self-interested secondary users (SUs) desire to maximize their own throughput. They compete with each other for transmit time once the absence of primary users (PUs) is detected. To satisfy the requirement of PU protection, on the other hand, they have to form some coalitions and cooperate to conduct spectrum sensing. Such dilemma of SUs between competition and cooperation motivates us to study two interesting issues: 1) how to appropriately form some coalitions for cooperative spectrum sensing (CSS) and 2) how to share transmit time among SUs. We jointly consider these two issues, and propose a noncooperative game model with 2-D strategies. The first dimension determines coalition formation, and the second indicates transmit time allocation. Considering the complexity of solving this game, we decompose the game into two more tractable ones: one deals with the formation of CSS coalitions, and the other focuses on the allocation of transmit time. We characterize the Nash equilibria (NEs) of both games, and show that the combination of these two NEs corresponds to the NE of the original game. We also develop a distributed algorithm to achieve a desirable NE of the original game. When this NE is achieved, the SUs obtain a Dhp-stable coalition structure and a fair transmit time allocation. Numerical results verify our analyses, and demonstrate the effectiveness of our algorithm.

Awareware: Narrowcasting Attributes for Selective Attention, Privacy, and Multipresence

NASA Astrophysics Data System (ADS)

Cohen, Michael; Newton Fernando, Owen Noel

The domain of cscw, computer-supported collaborative work, and DSC, distributed synchronous collaboration, spans real-time interactive multiuser systems, shared information spaces, and applications for teleexistence and artificial reality, including collaborative virtual environments ( cves) (Benford et al., 2001). As presence awareness systems emerge, it is important to develop appropriate interfaces and architectures for managing multimodal multiuser systems. Especially in consideration of the persistent connectivity enabled by affordable networked communication, shared distributed environments require generalized control of media streams, techniques to control source → sink transmissions in synchronous groupware, including teleconferences and chatspaces, online role-playing games, and virtual concerts.

A cooperative game framework for detecting overlapping communities in social networks

NASA Astrophysics Data System (ADS)

Jonnalagadda, Annapurna; Kuppusamy, Lakshmanan

2018-02-01

Community detection in social networks is a challenging and complex task, which received much attention from researchers of multiple domains in recent years. The evolution of communities in social networks happens merely due to the self-interest of the nodes. The interesting feature of community structure in social networks is the multi membership of the nodes resulting in overlapping communities. Assuming the nodes of the social network as self-interested players, the dynamics of community formation can be captured in the form of a game. In this paper, we propose a greedy algorithm, namely, Weighted Graph Community Game (WGCG), in order to model the interactions among the self-interested nodes of the social network. The proposed algorithm employs the Shapley value mechanism to discover the inherent communities of the underlying social network. The experimental evaluation on the real-world and synthetic benchmark networks demonstrates that the performance of the proposed algorithm is superior to the state-of-the-art overlapping community detection algorithms.

A Markov game theoretic data fusion approach for cyber situational awareness

NASA Astrophysics Data System (ADS)

Shen, Dan; Chen, Genshe; Cruz, Jose B., Jr.; Haynes, Leonard; Kruger, Martin; Blasch, Erik

2007-04-01

This paper proposes an innovative data-fusion/ data-mining game theoretic situation awareness and impact assessment approach for cyber network defense. Alerts generated by Intrusion Detection Sensors (IDSs) or Intrusion Prevention Sensors (IPSs) are fed into the data refinement (Level 0) and object assessment (L1) data fusion components. High-level situation/threat assessment (L2/L3) data fusion based on Markov game model and Hierarchical Entity Aggregation (HEA) are proposed to refine the primitive prediction generated by adaptive feature/pattern recognition and capture new unknown features. A Markov (Stochastic) game method is used to estimate the belief of each possible cyber attack pattern. Game theory captures the nature of cyber conflicts: determination of the attacking-force strategies is tightly coupled to determination of the defense-force strategies and vice versa. Also, Markov game theory deals with uncertainty and incompleteness of available information. A software tool is developed to demonstrate the performance of the high level information fusion for cyber network defense situation and a simulation example shows the enhanced understating of cyber-network defense.

Combinatorial optimization games

DOE Office of Scientific and Technical Information (OSTI.GOV)

Deng, X.; Ibaraki, Toshihide; Nagamochi, Hiroshi

1997-06-01

We introduce a general integer programming formulation for a class of combinatorial optimization games, which immediately allows us to improve the algorithmic result for finding amputations in the core (an important solution concept in cooperative game theory) of the network flow game on simple networks by Kalai and Zemel. An interesting result is a general theorem that the core for this class of games is nonempty if and only if a related linear program has an integer optimal solution. We study the properties for this mathematical condition to hold for several interesting problems, and apply them to resolve algorithmic andmore » complexity issues for their cores along the line as put forward in: decide whether the core is empty; if the core is empty, find an imputation in the core; given an imputation x, test whether x is in the core. We also explore the properties of totally balanced games in this succinct formulation of cooperative games.« less

A virtual pebble game to ensemble average graph rigidity.

PubMed

González, Luis C; Wang, Hui; Livesay, Dennis R; Jacobs, Donald J

2015-01-01

The body-bar Pebble Game (PG) algorithm is commonly used to calculate network rigidity properties in proteins and polymeric materials. To account for fluctuating interactions such as hydrogen bonds, an ensemble of constraint topologies are sampled, and average network properties are obtained by averaging PG characterizations. At a simpler level of sophistication, Maxwell constraint counting (MCC) provides a rigorous lower bound for the number of internal degrees of freedom (DOF) within a body-bar network, and it is commonly employed to test if a molecular structure is globally under-constrained or over-constrained. MCC is a mean field approximation (MFA) that ignores spatial fluctuations of distance constraints by replacing the actual molecular structure by an effective medium that has distance constraints globally distributed with perfect uniform density. The Virtual Pebble Game (VPG) algorithm is a MFA that retains spatial inhomogeneity in the density of constraints on all length scales. Network fluctuations due to distance constraints that may be present or absent based on binary random dynamic variables are suppressed by replacing all possible constraint topology realizations with the probabilities that distance constraints are present. The VPG algorithm is isomorphic to the PG algorithm, where integers for counting "pebbles" placed on vertices or edges in the PG map to real numbers representing the probability to find a pebble. In the VPG, edges are assigned pebble capacities, and pebble movements become a continuous flow of probability within the network. Comparisons between the VPG and average PG results over a test set of proteins and disordered lattices demonstrate the VPG quantitatively estimates the ensemble average PG results well. The VPG performs about 20% faster than one PG, and it provides a pragmatic alternative to averaging PG rigidity characteristics over an ensemble of constraint topologies. The utility of the VPG falls in between the most accurate but slowest method of ensemble averaging over hundreds to thousands of independent PG runs, and the fastest but least accurate MCC.

A network-based dynamical ranking system for competitive sports

NASA Astrophysics Data System (ADS)

Motegi, Shun; Masuda, Naoki

2012-12-01

From the viewpoint of networks, a ranking system for players or teams in sports is equivalent to a centrality measure for sports networks, whereby a directed link represents the result of a single game. Previously proposed network-based ranking systems are derived from static networks, i.e., aggregation of the results of games over time. However, the score of a player (or team) fluctuates over time. Defeating a renowned player in the peak performance is intuitively more rewarding than defeating the same player in other periods. To account for this factor, we propose a dynamic variant of such a network-based ranking system and apply it to professional men's tennis data. We derive a set of linear online update equations for the score of each player. The proposed ranking system predicts the outcome of the future games with a higher accuracy than the static counterparts.

Transfer of conflict and cooperation from experienced games to new games: a connectionist model of learning

PubMed Central

Spiliopoulos, Leonidas

2015-01-01

The question of whether, and if so how, learning can be transfered from previously experienced games to novel games has recently attracted the attention of the experimental game theory literature. Existing research presumes that learning operates over actions, beliefs or decision rules. This study instead uses a connectionist approach that learns a direct mapping from game payoffs to a probability distribution over own actions. Learning is operationalized as a backpropagation rule that adjusts the weights of feedforward neural networks in the direction of increasing the probability of an agent playing a myopic best response to the last game played. One advantage of this approach is that it expands the scope of the model to any possible n × n normal-form game allowing for a comprehensive model of transfer of learning. Agents are exposed to games drawn from one of seven classes of games with significantly different strategic characteristics and then forced to play games from previously unseen classes. I find significant transfer of learning, i.e., behavior that is path-dependent, or conditional on the previously seen games. Cooperation is more pronounced in new games when agents are previously exposed to games where the incentive to cooperate is stronger than the incentive to compete, i.e., when individual incentives are aligned. Prior exposure to Prisoner's dilemma, zero-sum and discoordination games led to a significant decrease in realized payoffs for all the game classes under investigation. A distinction is made between superficial and deep transfer of learning both—the former is driven by superficial payoff similarities between games, the latter by differences in the incentive structures or strategic implications of the games. I examine whether agents learn to play the Nash equilibria of games, how they select amongst multiple equilibria, and whether they transfer Nash equilibrium behavior to unseen games. Sufficient exposure to a strategically heterogeneous set of games is found to be a necessary condition for deep learning (and transfer) across game classes. Paradoxically, superficial transfer of learning is shown to lead to better outcomes than deep transfer for a wide range of game classes. The simulation results corroborate important experimental findings with human subjects, and make several novel predictions that can be tested experimentally. PMID:25873855

Cell Selection Game for Densely-Deployed Sensor and Mobile Devices In 5G Networks Integrating Heterogeneous Cells and the Internet of Things.

PubMed

Wang, Lusheng; Wang, Yamei; Ding, Zhizhong; Wang, Xiumin

2015-09-18

With the rapid development of wireless networking technologies, the Internet of Things and heterogeneous cellular networks (HCNs) tend to be integrated to form a promising wireless network paradigm for 5G. Hyper-dense sensor and mobile devices will be deployed under the coverage of heterogeneous cells, so that each of them could freely select any available cell covering it and compete for resource with others selecting the same cell, forming a cell selection (CS) game between these devices. Since different types of cells usually share the same portion of the spectrum, devices selecting overlapped cells can experience severe inter-cell interference (ICI). In this article, we study the CS game among a large amount of densely-deployed sensor and mobile devices for their uplink transmissions in a two-tier HCN. ICI is embedded with the traditional congestion game (TCG), forming a congestion game with ICI (CGI) and a congestion game with capacity (CGC). For the three games above, we theoretically find the circular boundaries between the devices selecting the macrocell and those selecting the picocells, indicated by the pure strategy Nash equilibria (PSNE). Meanwhile, through a number of simulations with different picocell radii and different path loss exponents, the collapse of the PSNE impacted by severe ICI (i.e., a large number of picocell devices change their CS preferences to the macrocell) is profoundly revealed, and the collapse points are identified.

Cell Selection Game for Densely-Deployed Sensor and Mobile Devices In 5G Networks Integrating Heterogeneous Cells and the Internet of Things

PubMed Central

Wang, Lusheng; Wang, Yamei; Ding, Zhizhong; Wang, Xiumin

2015-01-01

With the rapid development of wireless networking technologies, the Internet of Things and heterogeneous cellular networks (HCNs) tend to be integrated to form a promising wireless network paradigm for 5G. Hyper-dense sensor and mobile devices will be deployed under the coverage of heterogeneous cells, so that each of them could freely select any available cell covering it and compete for resource with others selecting the same cell, forming a cell selection (CS) game between these devices. Since different types of cells usually share the same portion of the spectrum, devices selecting overlapped cells can experience severe inter-cell interference (ICI). In this article, we study the CS game among a large amount of densely-deployed sensor and mobile devices for their uplink transmissions in a two-tier HCN. ICI is embedded with the traditional congestion game (TCG), forming a congestion game with ICI (CGI) and a congestion game with capacity (CGC). For the three games above, we theoretically find the circular boundaries between the devices selecting the macrocell and those selecting the picocells, indicated by the pure strategy Nash equilibria (PSNE). Meanwhile, through a number of simulations with different picocell radii and different path loss exponents, the collapse of the PSNE impacted by severe ICI (i.e., a large number of picocell devices change their CS preferences to the macrocell) is profoundly revealed, and the collapse points are identified. PMID:26393617

Networks and games for precision medicine.

PubMed

Biane, Célia; Delaplace, Franck; Klaudel, Hanna

2016-12-01

Recent advances in omics technologies provide the leverage for the emergence of precision medicine that aims at personalizing therapy to patient. In this undertaking, computational methods play a central role for assisting physicians in their clinical decision-making by combining data analysis and systems biology modelling. Complex diseases such as cancer or diabetes arise from the intricate interplay of various biological molecules. Therefore, assessing drug efficiency requires to study the effects of elementary perturbations caused by diseases on relevant biological networks. In this paper, we propose a computational framework called Network-Action Game applied to best drug selection problem combining Game Theory and discrete models of dynamics (Boolean networks). Decision-making is modelled using Game Theory that defines the process of drug selection among alternative possibilities, while Boolean networks are used to model the effects of the interplay between disease and drugs actions on the patient's molecular system. The actions/strategies of disease and drugs are focused on arc alterations of the interactome. The efficiency of this framework has been evaluated for drug prediction on a model of breast cancer signalling. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

The Effects of Sacred Value Networks Within an Evolutionary, Adversarial Game

NASA Astrophysics Data System (ADS)

McCalla, Scott G.; Short, Martin B.; Brantingham, P. Jeffrey

2013-05-01

The effects of personal relationships and shared ideologies on levels of crime and the formation of criminal coalitions are studied within the context of an adversarial, evolutionary game first introduced in Short et al. (Phys. Rev. E 82:066114, 2010). Here, we interpret these relationships as connections on a graph of N players. These connections are then used in a variety of ways to define each player's "sacred value network"—groups of individuals that are subject to special consideration or treatment by that player. We explore the effects on the dynamics of the system that these networks introduce, through various forms of protection from both victimization and punishment. Under local protection, these networks introduce a new fixed point within the game dynamics, which we find through a continuum approximation of the discrete game. Under more complicated, extended protection, we numerically observe the emergence of criminal coalitions, or "gangs". We also find that a high-crime steady state is much more frequent in the context of extended protection networks, in both the case of Erdős-Rényi and small world random graphs.

Discovering Multimodal Behavior in Ms. Pac-Man through Evolution of Modular Neural Networks.

PubMed

Schrum, Jacob; Miikkulainen, Risto

2016-03-12

Ms. Pac-Man is a challenging video game in which multiple modes of behavior are required: Ms. Pac-Man must escape ghosts when they are threats and catch them when they are edible, in addition to eating all pills in each level. Past approaches to learning behavior in Ms. Pac-Man have treated the game as a single task to be learned using monolithic policy representations. In contrast, this paper uses a framework called Modular Multi-objective NEAT (MM-NEAT) to evolve modular neural networks. Each module defines a separate behavior. The modules are used at different times according to a policy that can be human-designed (i.e. Multitask) or discovered automatically by evolution. The appropriate number of modules can be fixed or discovered using a genetic operator called Module Mutation. Several versions of Module Mutation are evaluated in this paper. Both fixed modular networks and Module Mutation networks outperform monolithic networks and Multitask networks. Interestingly, the best networks dedicate modules to critical behaviors (such as escaping when surrounded after luring ghosts near a power pill) that do not follow the customary division of the game into chasing edible and escaping threat ghosts. The results demonstrate that MM-NEAT can discover interesting and effective behavior for agents in challenging games.

Discovering Multimodal Behavior in Ms. Pac-Man through Evolution of Modular Neural Networks

PubMed Central

Schrum, Jacob; Miikkulainen, Risto

2015-01-01

Ms. Pac-Man is a challenging video game in which multiple modes of behavior are required: Ms. Pac-Man must escape ghosts when they are threats and catch them when they are edible, in addition to eating all pills in each level. Past approaches to learning behavior in Ms. Pac-Man have treated the game as a single task to be learned using monolithic policy representations. In contrast, this paper uses a framework called Modular Multi-objective NEAT (MM-NEAT) to evolve modular neural networks. Each module defines a separate behavior. The modules are used at different times according to a policy that can be human-designed (i.e. Multitask) or discovered automatically by evolution. The appropriate number of modules can be fixed or discovered using a genetic operator called Module Mutation. Several versions of Module Mutation are evaluated in this paper. Both fixed modular networks and Module Mutation networks outperform monolithic networks and Multitask networks. Interestingly, the best networks dedicate modules to critical behaviors (such as escaping when surrounded after luring ghosts near a power pill) that do not follow the customary division of the game into chasing edible and escaping threat ghosts. The results demonstrate that MM-NEAT can discover interesting and effective behavior for agents in challenging games. PMID:27030803

The Anatomy of the Global Football Player Transfer Network: Club Functionalities versus Network Properties

PubMed Central

2016-01-01

Professional association football is a game of talent. The success of a professional club hinges largely on its ability of assembling the best team. Building on a dataset of player transfer records among more than 400 clubs in 24 world-wide top class leagues from 2011 to 2015, this study aims to relate a club’s success to its activities in the player transfer market from a network perspective. We confirm that modern professional football is indeed a money game, in which larger investment spent on the acquisition of talented players generally yields better team performance. However, further investigation shows that professional football clubs can actually play different strategies in surviving or even excelling this game, and the success of strategies is strongly associated to their network properties in the football player transfer network. PMID:27253198

The Anatomy of the Global Football Player Transfer Network: Club Functionalities versus Network Properties.

PubMed

Liu, Xiao Fan; Liu, Yu-Liang; Lu, Xin-Hang; Wang, Qi-Xuan; Wang, Tong-Xing

2016-01-01

Professional association football is a game of talent. The success of a professional club hinges largely on its ability of assembling the best team. Building on a dataset of player transfer records among more than 400 clubs in 24 world-wide top class leagues from 2011 to 2015, this study aims to relate a club's success to its activities in the player transfer market from a network perspective. We confirm that modern professional football is indeed a money game, in which larger investment spent on the acquisition of talented players generally yields better team performance. However, further investigation shows that professional football clubs can actually play different strategies in surviving or even excelling this game, and the success of strategies is strongly associated to their network properties in the football player transfer network.

Path synthesis of four-bar mechanisms using synergy of polynomial neural network and Stackelberg game theory

NASA Astrophysics Data System (ADS)

Ahmadi, Bahman; Nariman-zadeh, Nader; Jamali, Ali

2017-06-01

In this article, a novel approach based on game theory is presented for multi-objective optimal synthesis of four-bar mechanisms. The multi-objective optimization problem is modelled as a Stackelberg game. The more important objective function, tracking error, is considered as the leader, and the other objective function, deviation of the transmission angle from 90° (TA), is considered as the follower. In a new approach, a group method of data handling (GMDH)-type neural network is also utilized to construct an approximate model for the rational reaction set (RRS) of the follower. Using the proposed game-theoretic approach, the multi-objective optimal synthesis of a four-bar mechanism is then cast into a single-objective optimal synthesis using the leader variables and the obtained RRS of the follower. The superiority of using the synergy game-theoretic method of Stackelberg with a GMDH-type neural network is demonstrated for two case studies on the synthesis of four-bar mechanisms.

Mastering the game of Go without human knowledge.

PubMed

Silver, David; Schrittwieser, Julian; Simonyan, Karen; Antonoglou, Ioannis; Huang, Aja; Guez, Arthur; Hubert, Thomas; Baker, Lucas; Lai, Matthew; Bolton, Adrian; Chen, Yutian; Lillicrap, Timothy; Hui, Fan; Sifre, Laurent; van den Driessche, George; Graepel, Thore; Hassabis, Demis

2017-10-18

A long-standing goal of artificial intelligence is an algorithm that learns, tabula rasa, superhuman proficiency in challenging domains. Recently, AlphaGo became the first program to defeat a world champion in the game of Go. The tree search in AlphaGo evaluated positions and selected moves using deep neural networks. These neural networks were trained by supervised learning from human expert moves, and by reinforcement learning from self-play. Here we introduce an algorithm based solely on reinforcement learning, without human data, guidance or domain knowledge beyond game rules. AlphaGo becomes its own teacher: a neural network is trained to predict AlphaGo's own move selections and also the winner of AlphaGo's games. This neural network improves the strength of the tree search, resulting in higher quality move selection and stronger self-play in the next iteration. Starting tabula rasa, our new program AlphaGo Zero achieved superhuman performance, winning 100-0 against the previously published, champion-defeating AlphaGo.

Mastering the game of Go without human knowledge

NASA Astrophysics Data System (ADS)

Silver, David; Schrittwieser, Julian; Simonyan, Karen; Antonoglou, Ioannis; Huang, Aja; Guez, Arthur; Hubert, Thomas; Baker, Lucas; Lai, Matthew; Bolton, Adrian; Chen, Yutian; Lillicrap, Timothy; Hui, Fan; Sifre, Laurent; van den Driessche, George; Graepel, Thore; Hassabis, Demis

2017-10-01

A long-standing goal of artificial intelligence is an algorithm that learns, tabula rasa, superhuman proficiency in challenging domains. Recently, AlphaGo became the first program to defeat a world champion in the game of Go. The tree search in AlphaGo evaluated positions and selected moves using deep neural networks. These neural networks were trained by supervised learning from human expert moves, and by reinforcement learning from self-play. Here we introduce an algorithm based solely on reinforcement learning, without human data, guidance or domain knowledge beyond game rules. AlphaGo becomes its own teacher: a neural network is trained to predict AlphaGo’s own move selections and also the winner of AlphaGo’s games. This neural network improves the strength of the tree search, resulting in higher quality move selection and stronger self-play in the next iteration. Starting tabula rasa, our new program AlphaGo Zero achieved superhuman performance, winning 100-0 against the previously published, champion-defeating AlphaGo.

Addiction to Internet Use, Online Gaming, and Online Social Networking Among Young Adults in China, Singapore, and the United States.

PubMed

Tang, Catherine So-Kum; Koh, Yee Woen; Gan, YiQun

2017-11-01

The current study investigated the rates of addictions to Internet use, online gaming, and online social networking as well as their associations with depressive symptoms among young adults in China, Singapore, and the United States. A total of 3267 undergraduate students were recruited. Psychological instruments were used to assess various Internet-related addictions and depressive symptoms. Male students were more addicted to Internet and online gaming whereas female students were more addicted to online social networking. Compared with students in the United States, Chinese and Singaporean students were more addicted to Internet use and online social networking but less to online gaming. The odds of depression among students with addiction to various Internet-related addictions were highest in China. Internet-related addiction is a new public health concern of young adults, especially in the Asia-Pacific regions. It is found to associate with depressive symptoms. Strategies should address this phenomenon with attention to specific needs of gender and region while managing mood disturbances.

Simultaneously selecting appropriate partners for gaming and strategy adaptation to enhance network reciprocity in the prisoner's dilemma

NASA Astrophysics Data System (ADS)

Tanimoto, Jun

2014-01-01

Network reciprocity is one mechanism for adding social viscosity, which leads to cooperative equilibrium in 2 × 2 prisoner's dilemma games. Previous studies have shown that cooperation can be enhanced by using a skewed, rather than a random, selection of partners for either strategy adaptation or the gaming process. Here we show that combining both processes for selecting a gaming partner and an adaptation partner further enhances cooperation, provided that an appropriate selection rule and parameters are adopted. We also show that this combined model significantly enhances cooperation by reducing the degree of activity in the underlying network; we measure the degree of activity with a quantity called effective degree. More precisely, during the initial evolutionary stage in which the global cooperation fraction declines because initially allocated cooperators becoming defectors, the model shows that weak cooperative clusters perish and only a few strong cooperative clusters survive. This finding is the most important key to attaining significant network reciprocity.

25 CFR 290.11 - May an Indian tribe distribute per capita payments from net gaming revenues derived from either...

Code of Federal Regulations, 2010 CFR

2010-04-01

... 25 Indians 1 2010-04-01 2010-04-01 false May an Indian tribe distribute per capita payments from net gaming revenues derived from either Class II or Class III gaming without a tribal revenue... net gaming revenues derived from either Class II or Class III gaming without a tribal revenue...

Spatial-Temporal Reasoning Applications of Computational Intelligence in the Game of Go and Computer Networks

DTIC Science & Technology

2012-01-01

dimensionality, Tesauro used a backpropagation- based , three-layer neural network and implemented the outcome from a self-play game as the reinforcement signal...a school of fish, flock of birds, and colony of ants. Our literature review reveals that no one has used PSO to train the neural network ...trained with a variant of PSO called cellular PSO (CPSO). CSRN is a supervised learning neural network (SLNN). The proposed algorithm for the

Modelling and strategy optimisation for a kind of networked evolutionary games with memories under the bankruptcy mechanism

NASA Astrophysics Data System (ADS)

Fu, Shihua; Li, Haitao; Zhao, Guodong

2018-05-01

This paper investigates the evolutionary dynamic and strategy optimisation for a kind of networked evolutionary games whose strategy updating rules incorporate 'bankruptcy' mechanism, and the situation that each player's bankruptcy is due to the previous continuous low profits gaining from the game is considered. First, by using semi-tensor product of matrices method, the evolutionary dynamic of this kind of games is expressed as a higher order logical dynamic system and then converted into its algebraic form, based on which, the evolutionary dynamic of the given games can be discussed. Second, the strategy optimisation problem is investigated, and some free-type control sequences are designed to maximise the total payoff of the whole game. Finally, an illustrative example is given to show that our new results are very effective.

Learning to play Go using recursive neural networks.

PubMed

Wu, Lin; Baldi, Pierre

2008-11-01

Go is an ancient board game that poses unique opportunities and challenges for artificial intelligence. Currently, there are no computer Go programs that can play at the level of a good human player. However, the emergence of large repositories of games is opening the door for new machine learning approaches to address this challenge. Here we develop a machine learning approach to Go, and related board games, focusing primarily on the problem of learning a good evaluation function in a scalable way. Scalability is essential at multiple levels, from the library of local tactical patterns, to the integration of patterns across the board, to the size of the board itself. The system we propose is capable of automatically learning the propensity of local patterns from a library of games. Propensity and other local tactical information are fed into recursive neural networks, derived from a probabilistic Bayesian network architecture. The recursive neural networks in turn integrate local information across the board in all four cardinal directions and produce local outputs that represent local territory ownership probabilities. The aggregation of these probabilities provides an effective strategic evaluation function that is an estimate of the expected area at the end, or at various other stages, of the game. Local area targets for training can be derived from datasets of games played by human players. In this approach, while requiring a learning time proportional to N(4), skills learned on a board of size N(2) can easily be transferred to boards of other sizes. A system trained using only 9 x 9 amateur game data performs surprisingly well on a test set derived from 19 x 19 professional game data. Possible directions for further improvements are briefly discussed.

Modeling Attrition in Organizations from Email Communication

DTIC Science & Technology

2013-09-08

networks [17]. A particular example is the video - gaming industry, a huge and growing market around the world, valued at about $65 billion in 2011 [18...Symposium, 2007. ANSS ’07. 40th Annual, march 2007, pp. 33 –40. [18] T. R. Corporation, “Factbox: A look at the $65 billion video games industry,” http...online multiplayer games , user involvement and movement in online social networking plat- forms, and employee turnover within an organization. At

Beyond the Player: A User-Centered Approach to Analyzing Digital Games and Players Using Actor-Network Theory

ERIC Educational Resources Information Center

Hung, Aaron Chia Yuan

2016-01-01

The paper uses actor-network theory (ANT) to analyze the sociotechnical networks of three groups of adolescents who played online games in different physical and social contexts. These include: an internet café, which allowed the players to be co-present; a personal laptop, which gave the player more control over how he played; and at home through…

Evaluation of a Web-Based Social Network Electronic Game in Enhancing Mental Health Literacy for Young People

PubMed Central

Li, Tim MH; Wong, Paul WC; Lai, Eliza SY; Yip, Paul SF

2013-01-01

Background Internet-based learning programs provide people with massive health care information and self-help guidelines on improving their health. The advent of Web 2.0 and social networks renders significant flexibility to embedding highly interactive components, such as games, to foster learning processes. The effectiveness of game-based learning on social networks has not yet been fully evaluated. Objectives The aim of this study was to assess the effectiveness of a fully automated, Web-based, social network electronic game on enhancing mental health knowledge and problem-solving skills of young people. We investigated potential motivational constructs directly affecting the learning outcome. Gender differences in learning outcome and motivation were also examined. Methods A pre/posttest design was used to evaluate the fully automated Web-based intervention. Participants, recruited from a closed online user group, self-assessed their mental health literacy and motivational constructs before and after completing the game within a 3-week period. The electronic game was designed according to cognitive-behavioral approaches. Completers and intent-to-treat analyses, using multiple imputation for missing data, were performed. Regression analysis with backward selection was employed when examining the relationship between knowledge enhancement and motivational constructs. Results The sample included 73 undergraduates (42 females) for completers analysis. The gaming approach was effective in enhancing young people’s mental health literacy (d=0.65). The finding was also consistent with the intent-to-treat analysis, which included 127 undergraduates (75 females). No gender differences were found in learning outcome (P=.97). Intrinsic goal orientation was the primary factor in learning motivation, whereas test anxiety was successfully alleviated in the game setting. No gender differences were found on any learning motivation subscales (P>.10). We also found that participants’ self-efficacy for learning and performance, as well as test anxiety, significantly affected their learning outcomes, whereas other motivational subscales were statistically nonsignificant. Conclusions Electronic games implemented through social networking sites appear to effectively enhance users’ mental health literacy. PMID:23676714

Micro-economic analysis of the physical constrained markets: game theory application to competitive electricity markets

NASA Astrophysics Data System (ADS)

Bompard, E.; Ma, Y. C.; Ragazzi, E.

2006-03-01

Competition has been introduced in the electricity markets with the goal of reducing prices and improving efficiency. The basic idea which stays behind this choice is that, in competitive markets, a greater quantity of the good is exchanged at a lower price, leading to higher market efficiency. Electricity markets are pretty different from other commodities mainly due to the physical constraints related to the network structure that may impact the market performance. The network structure of the system on which the economic transactions need to be undertaken poses strict physical and operational constraints. Strategic interactions among producers that game the market with the objective of maximizing their producer surplus must be taken into account when modeling competitive electricity markets. The physical constraints, specific of the electricity markets, provide additional opportunity of gaming to the market players. Game theory provides a tool to model such a context. This paper discussed the application of game theory to physical constrained electricity markets with the goal of providing tools for assessing the market performance and pinpointing the critical network constraints that may impact the market efficiency. The basic models of game theory specifically designed to represent the electricity markets will be presented. IEEE30 bus test system of the constrained electricity market will be discussed to show the network impacts on the market performances in presence of strategic bidding behavior of the producers.

Asynchronous updates can promote the evolution of cooperation on multiplex networks

NASA Astrophysics Data System (ADS)

Allen, James M.; Hoyle, Rebecca B.

2017-04-01

We study the importance to the frequency of cooperation of the choice of updating strategies in a game played asynchronously or synchronously across layers in a multiplex network. Updating asynchronously in the public goods game leads to higher frequencies of cooperation compared to synchronous updates. How large this effect is depends on the sensitivity of the game dynamics to changes in the number of cooperators surrounding a player, with the largest effect observed when players payoffs are small. The discovery of this effect enhances understanding of cooperation on multiplex networks, and demonstrates a new way to maintain cooperation in these systems.

On Tradeoffs between Trust and Survivability using a Game Theoretic Approach

DTIC Science & Technology

2016-04-13

On Tradeoffs between Trust and Survivability using a Game Theoretic Approach Jin-Hee Cho and Ananthram Swami U.S. Army Research Laboratory...introduces a game theoretic approach, namely Aoyagi’s game theory based on positive collusion of players. This approach improves group trust by...communication and networking field [17]. We employ a game theoretic approach, namely Aoyagi’s game theory [2], to introduce the concept of positive

Evolutionary games on multilayer networks: a colloquium

NASA Astrophysics Data System (ADS)

Wang, Zhen; Wang, Lin; Szolnoki, Attila; Perc, Matjaž

2015-05-01

Networks form the backbone of many complex systems, ranging from the Internet to human societies. Accordingly, not only is the range of our interactions limited and thus best described and modeled by networks, it is also a fact that the networks that are an integral part of such models are often interdependent or even interconnected. Networks of networks or multilayer networks are therefore a more apt description of social systems. This colloquium is devoted to evolutionary games on multilayer networks, and in particular to the evolution of cooperation as one of the main pillars of modern human societies. We first give an overview of the most significant conceptual differences between single-layer and multilayer networks, and we provide basic definitions and a classification of the most commonly used terms. Subsequently, we review fascinating and counterintuitive evolutionary outcomes that emerge due to different types of interdependencies between otherwise independent populations. The focus is on coupling through the utilities of players, through the flow of information, as well as through the popularity of different strategies on different network layers. The colloquium highlights the importance of pattern formation and collective behavior for the promotion of cooperation under adverse conditions, as well as the synergies between network science and evolutionary game theory.

Having mentors and campus social networks moderates the impact of worries and video gaming on depressive symptoms: a moderated mediation analysis

PubMed Central

2014-01-01

Background Easy access to the internet has spawned a wealth of research to investigate the effects of its use on depression. However, one limitation of many previous studies is that they disregard the interactive mechanisms of risk and protective factors. The aim of the present study was to investigate a resilience model in the relationship between worry, daily internet video game playing, daily sleep duration, mentors, social networks and depression, using a moderated mediation analysis. Methods 6068 Korean undergraduate and graduate students participated in this study. The participants completed a web-based mental health screening questionnaire including the Beck Depression Inventory (BDI) and information about number of worries, number of mentors, number of campus social networks, daily sleep duration, daily amount of internet video game playing and daily amount of internet searching on computer or smartphone. A moderated mediation analysis was carried out using the PROCESS macro which allowed the inclusion of mediators and moderator in the same model. Results The results showed that the daily amount of internet video game playing and daily sleep duration partially mediated the association between the number of worries and the severity of depression. In addition, the mediating effect of the daily amount of internet video game playing was moderated by both the number of mentors and the number of campus social networks. Conclusions The current findings indicate that the negative impact of worry on depression through internet video game playing can be buffered when students seek to have a number of mentors and campus social networks. Interventions should therefore target individuals who have higher number of worries but seek only a few mentors or campus social networks. Social support via campus mentorship and social networks ameliorate the severity of depression in university students. PMID:24884864

Using a TV Game Show to Explain the Concept of a Dominant Strategy.

ERIC Educational Resources Information Center

Trandel, Gregory A.

1999-01-01

Illustrates the game-theory concept of a dominant strategy using the MTV-network game show "Singled Out." Describes how the game show works and why this makes it attractive as an example of strategic behavior. Presents examples of how the show is used in class. (DSK)

The Development of Attention Skills in Action Video Game Players

ERIC Educational Resources Information Center

Dye, M. W. G.; Green, C. S.; Bavelier, D.

2009-01-01

Previous research suggests that action video game play improves attentional resources, allowing gamers to better allocate their attention across both space and time. In order to further characterize the plastic changes resulting from playing these video games, we administered the Attentional Network Test (ANT) to action game players and…

Mapping Learning and Game Mechanics for Serious Games Analysis

ERIC Educational Resources Information Center

Arnab, Sylvester; Lim, Theodore; Carvalho, Maira B.; Bellotti, Francesco; de Freitas, Sara; Louchart, Sandy; Suttie, Neil; Berta, Riccardo; De Gloria, Alessandro

2015-01-01

Although there is a consensus on the instructional potential of Serious Games (SGs), there is still a lack of methodologies and tools not only for design but also to support analysis and assessment. Filling this gap is one of the main aims of the Games and Learning Alliance (http://www.galanoe.eu) European Network of Excellence on Serious Games,…

Identifying MMORPG Bots: A Traffic Analysis Approach

NASA Astrophysics Data System (ADS)

Chen, Kuan-Ta; Jiang, Jhih-Wei; Huang, Polly; Chu, Hao-Hua; Lei, Chin-Laung; Chen, Wen-Chin

2008-12-01

Massively multiplayer online role playing games (MMORPGs) have become extremely popular among network gamers. Despite their success, one of MMORPG's greatest challenges is the increasing use of game bots, that is, autoplaying game clients. The use of game bots is considered unsportsmanlike and is therefore forbidden. To keep games in order, game police, played by actual human players, often patrol game zones and question suspicious players. This practice, however, is labor-intensive and ineffective. To address this problem, we analyze the traffic generated by human players versus game bots and propose general solutions to identify game bots. Taking Ragnarok Online as our subject, we study the traffic generated by human players and game bots. We find that their traffic is distinguishable by 1) the regularity in the release time of client commands, 2) the trend and magnitude of traffic burstiness in multiple time scales, and 3) the sensitivity to different network conditions. Based on these findings, we propose four strategies and two ensemble schemes to identify bots. Finally, we discuss the robustness of the proposed methods against countermeasures of bot developers, and consider a number of possible ways to manage the increasingly serious bot problem.

Attacker-defender game from a network science perspective

NASA Astrophysics Data System (ADS)

Li, Ya-Peng; Tan, Suo-Yi; Deng, Ye; Wu, Jun

2018-05-01

Dealing with the protection of critical infrastructures, many game-theoretic methods have been developed to study the strategic interactions between defenders and attackers. However, most game models ignore the interrelationship between different components within a certain system. In this paper, we propose a simultaneous-move attacker-defender game model, which is a two-player zero-sum static game with complete information. The strategies and payoffs of this game are defined on the basis of the topology structure of the infrastructure system, which is represented by a complex network. Due to the complexity of strategies, the attack and defense strategies are confined by two typical strategies, namely, targeted strategy and random strategy. The simulation results indicate that in a scale-free network, the attacker virtually always attacks randomly in the Nash equilibrium. With a small cost-sensitive parameter, representing the degree to which costs increase with the importance of a target, the defender protects the hub targets with large degrees preferentially. When the cost-sensitive parameter exceeds a threshold, the defender switches to protecting nodes randomly. Our work provides a new theoretical framework to analyze the confrontations between the attacker and the defender on critical infrastructures and deserves further study.

Multi-language naming game

NASA Astrophysics Data System (ADS)

Zhou, Jianfeng; Lou, Yang; Chen, Guanrong; Tang, Wallace K. S.

2018-04-01

Naming game is a simulation-based experiment used to study the evolution of languages. The conventional naming game focuses on a single language. In this paper, a novel naming game model named multi-language naming game (MLNG) is proposed, where the agents are different-language speakers who cannot communicate with each other without a translator (interpreter) in between. The MLNG model is general, capable of managing k different languages with k ≥ 2. For illustration, the paper only discusses the MLNG with two different languages, and studies five representative network topologies, namely random-graph, WS small-world, NW small-world, scale-free, and random-triangle topologies. Simulation and analysis results both show that: 1) using the network features and based on the proportion of translators the probability of establishing a conversation between two or three agents can be theoretically estimated; 2) the relationship between the convergence speed and the proportion of translators has a power-law-like relation; 3) different agents require different memory sizes, thus a local memory allocation rule is recommended for saving memory resources. The new model and new findings should be useful for further studies of naming games and for better understanding of languages evolution from a dynamical network perspective.

Local Nash equilibrium in social networks.

PubMed

Zhang, Yichao; Aziz-Alaoui, M A; Bertelle, Cyrille; Guan, Jihong

2014-08-29

Nash equilibrium is widely present in various social disputes. As of now, in structured static populations, such as social networks, regular, and random graphs, the discussions on Nash equilibrium are quite limited. In a relatively stable static gaming network, a rational individual has to comprehensively consider all his/her opponents' strategies before they adopt a unified strategy. In this scenario, a new strategy equilibrium emerges in the system. We define this equilibrium as a local Nash equilibrium. In this paper, we present an explicit definition of the local Nash equilibrium for the two-strategy games in structured populations. Based on the definition, we investigate the condition that a system reaches the evolutionary stable state when the individuals play the Prisoner's dilemma and snow-drift game. The local Nash equilibrium provides a way to judge whether a gaming structured population reaches the evolutionary stable state on one hand. On the other hand, it can be used to predict whether cooperators can survive in a system long before the system reaches its evolutionary stable state for the Prisoner's dilemma game. Our work therefore provides a theoretical framework for understanding the evolutionary stable state in the gaming populations with static structures.

Local Nash Equilibrium in Social Networks

PubMed Central

Zhang, Yichao; Aziz-Alaoui, M. A.; Bertelle, Cyrille; Guan, Jihong

2014-01-01

Nash equilibrium is widely present in various social disputes. As of now, in structured static populations, such as social networks, regular, and random graphs, the discussions on Nash equilibrium are quite limited. In a relatively stable static gaming network, a rational individual has to comprehensively consider all his/her opponents' strategies before they adopt a unified strategy. In this scenario, a new strategy equilibrium emerges in the system. We define this equilibrium as a local Nash equilibrium. In this paper, we present an explicit definition of the local Nash equilibrium for the two-strategy games in structured populations. Based on the definition, we investigate the condition that a system reaches the evolutionary stable state when the individuals play the Prisoner's dilemma and snow-drift game. The local Nash equilibrium provides a way to judge whether a gaming structured population reaches the evolutionary stable state on one hand. On the other hand, it can be used to predict whether cooperators can survive in a system long before the system reaches its evolutionary stable state for the Prisoner's dilemma game. Our work therefore provides a theoretical framework for understanding the evolutionary stable state in the gaming populations with static structures. PMID:25169150

Local Nash Equilibrium in Social Networks

NASA Astrophysics Data System (ADS)

Zhang, Yichao; Aziz-Alaoui, M. A.; Bertelle, Cyrille; Guan, Jihong

2014-08-01

Nash equilibrium is widely present in various social disputes. As of now, in structured static populations, such as social networks, regular, and random graphs, the discussions on Nash equilibrium are quite limited. In a relatively stable static gaming network, a rational individual has to comprehensively consider all his/her opponents' strategies before they adopt a unified strategy. In this scenario, a new strategy equilibrium emerges in the system. We define this equilibrium as a local Nash equilibrium. In this paper, we present an explicit definition of the local Nash equilibrium for the two-strategy games in structured populations. Based on the definition, we investigate the condition that a system reaches the evolutionary stable state when the individuals play the Prisoner's dilemma and snow-drift game. The local Nash equilibrium provides a way to judge whether a gaming structured population reaches the evolutionary stable state on one hand. On the other hand, it can be used to predict whether cooperators can survive in a system long before the system reaches its evolutionary stable state for the Prisoner's dilemma game. Our work therefore provides a theoretical framework for understanding the evolutionary stable state in the gaming populations with static structures.

Bribery games on inter-dependent regular networks.

PubMed

Verma, Prateek; Nandi, Anjan K; Sengupta, Supratim

2017-02-16

We examine a scenario of social conflict that is manifest during an interaction between government servants providing a service and citizens who are legally entitled to the service, using evolutionary game-theory in structured populations characterized by an inter-dependent network. Bribe-demands by government servants during such transactions, called harassment bribes, constitute a widespread form of corruption in many countries. We investigate the effect of varying bribe demand made by corrupt officials and the cost of complaining incurred by harassed citizens, on the proliferation of corrupt strategies in the population. We also examine how the connectivity of the various constituent networks affects the spread of corrupt officials in the population. We find that incidents of bribery can be considerably reduced in a network-structured populations compared to mixed populations. Interestingly, we also find that an optimal range for the connectivity of nodes in the citizen's network (signifying the degree of influence a citizen has in affecting the strategy of other citizens in the network) as well as the interaction network aids in the fixation of honest officers. Our results reveal the important role of network structure and connectivity in asymmetric games.

Coevolution of game and network structure with adjustable linking

NASA Astrophysics Data System (ADS)

Qin, Shao-Meng; Zhang, Guo-Yong; Chen, Yong

2009-12-01

Most papers about the evolutionary game on graph assume the statistic network structure. However, in the real world, social interaction could change the relationship among people. And the change of social structure will also affect people’s strategies. We build a coevolution model of prisoner’s dilemma game and network structure to study the dynamic interaction in the real world. Differing from other coevolution models, players rewire their network connections according to the density of cooperation and other players’ payoffs. We use a parameter α to control the effect of payoff in the process of rewiring. Based on the asynchronous update rule and Monte Carlo simulation, we find that, when players prefer to rewire their links to those who are richer, the temptation can increase the cooperation density.

Communication, opponents, and clan performance in online games: a social network approach.

PubMed

Lee, Hong Joo; Choi, Jaewon; Kim, Jong Woo; Park, Sung Joo; Gloor, Peter

2013-12-01

Online gamers form clans voluntarily to play together and to discuss their real and virtual lives. Although these clans have diverse goals, they seek to increase their rank in the game community by winning more battles. Communications among clan members and battles with other clans may influence the performance of a clan. In this study, we compared the effects of communication structure inside a clan, and battle networks among clans, with the performance of the clans. We collected battle histories, posts, and comments on clan pages from a Korean online game, and measured social network indices for communication and battle networks. Communication structures in terms of density and group degree centralization index had no significant association with clan performance. However, the centrality of clans in the battle network was positively related to the performance of the clan. If a clan had many battle opponents, the performance of the clan improved.

Communication, Opponents, and Clan Performance in Online Games: A Social Network Approach

PubMed Central

Lee, Hong Joo; Choi, Jaewon; Park, Sung Joo; Gloor, Peter

2013-01-01

Abstract Online gamers form clans voluntarily to play together and to discuss their real and virtual lives. Although these clans have diverse goals, they seek to increase their rank in the game community by winning more battles. Communications among clan members and battles with other clans may influence the performance of a clan. In this study, we compared the effects of communication structure inside a clan, and battle networks among clans, with the performance of the clans. We collected battle histories, posts, and comments on clan pages from a Korean online game, and measured social network indices for communication and battle networks. Communication structures in terms of density and group degree centralization index had no significant association with clan performance. However, the centrality of clans in the battle network was positively related to the performance of the clan. If a clan had many battle opponents, the performance of the clan improved. PMID:23745617

Interplay between cooperation-enhancing mechanisms in evolutionary games with tag-mediated interactions

NASA Astrophysics Data System (ADS)

Hadzibeganovic, Tarik; Stauffer, Dietrich; Han, Xiao-Pu

2018-04-01

Cooperation is fundamental for the long-term survival of biological, social, and technological networks. Previously, mechanisms for the enhancement of cooperation, such as network reciprocity, have largely been studied in isolation and with often inconclusive findings. Here, we present an evolutionary, multiagent-based, and spatially explicit computer model to specifically address the interactive interplay between such mechanisms. We systematically investigate the effects of phenotypic diversity, network structure, and rewards on cooperative behavior emerging in a population of reproducing artificial decision makers playing tag-mediated evolutionary games. Cooperative interactions are rewarded such that both the benefits of recipients and costs of donators are affected by the reward size. The reward size is determined by the number of cooperative acts occurring within a given reward time frame. Our computational experiments reveal that small reward frames promote unconditional cooperation in populations with both low and high diversity, whereas large reward frames lead to cycles of conditional and unconditional strategies at high but not at low diversity. Moreover, an interaction between rewards and spatial structure shows that relative to small reward frames, there is a strong difference between the frequency of conditional cooperators populating rewired versus non-rewired networks when the reward frame is large. Notably, in a less diverse population, the total number of defections is comparable across different network topologies, whereas in more diverse environments defections become more frequent in a regularly structured than in a rewired, small-world network of contacts. Acknowledging the importance of such interaction effects in social dilemmas will have inevitable consequences for the future design of cooperation-enhancing protocols in large-scale, distributed, and decentralized systems such as peer-to-peer networks.

Emergence of synchronization induced by the interplay between two prisoner's dilemma games with volunteering in small-world networks

NASA Astrophysics Data System (ADS)

Chen, Yong; Qin, Shao-Meng; Yu, Lianchun; Zhang, Shengli

2008-03-01

We studied synchronization between prisoner’s dilemma games with voluntary participation in two Newman-Watts small-world networks. It was found that there are three kinds of synchronization: partial phase synchronization, total phase synchronization, and complete synchronization, for varied coupling factors. Besides, two games can reach complete synchronization for the large enough coupling factor. We also discussed the effect of the coupling factor on the amplitude of oscillation of cooperator density.

Decelerated invasion and waning-moon patterns in public goods games with delayed distribution.

PubMed

Szolnoki, Attila; Perc, Matjaž

2013-05-01

We study the evolution of cooperation in the spatial public goods game, focusing on the effects that are brought about by the delayed distribution of goods that accumulate in groups due to the continuous investments of cooperators. We find that intermediate delays enhance network reciprocity because of a decelerated invasion of defectors, who are unable to reap the same high short-term benefits as they do in the absence of delayed distribution. Long delays, however, introduce a risk because the large accumulated wealth might fall into the wrong hands. Indeed, as soon as the curvature of a cooperative cluster turns negative, the engulfed defectors can collect the heritage of many generations of cooperators and by doing so start a waning-moon pattern that nullifies the benefits of decelerated invasion. Accidental meeting points of growing cooperative clusters may also act as triggers for the waning-moon effect, thus linking the success of cooperators with their propensity to fail in a rather bizarre way. Our results highlight that "investing in the future" is a good idea only if that future is sufficiently near and not likely to be burdened by inflation.

Social networks and cooperation in hunter-gatherers.

PubMed

Apicella, Coren L; Marlowe, Frank W; Fowler, James H; Christakis, Nicholas A

2012-01-25

Social networks show striking structural regularities, and both theory and evidence suggest that networks may have facilitated the development of large-scale cooperation in humans. Here, we characterize the social networks of the Hadza, a population of hunter-gatherers in Tanzania. We show that Hadza networks have important properties also seen in modernized social networks, including a skewed degree distribution, degree assortativity, transitivity, reciprocity, geographic decay and homophily. We demonstrate that Hadza camps exhibit high between-group and low within-group variation in public goods game donations. Network ties are also more likely between people who give the same amount, and the similarity in cooperative behaviour extends up to two degrees of separation. Social distance appears to be as important as genetic relatedness and physical proximity in explaining assortativity in cooperation. Our results suggest that certain elements of social network structure may have been present at an early point in human history. Also, early humans may have formed ties with both kin and non-kin, based in part on their tendency to cooperate. Social networks may thus have contributed to the emergence of cooperation.

A multimodal interface device for online board games designed for sight-impaired people.

PubMed

Caporusso, Nicholas; Mkrtchyan, Lusine; Badia, Leonardo

2010-03-01

Online games between remote opponents playing over computer networks are becoming a common activity of everyday life. However, computer interfaces for board games are usually based on the visual channel. For example, they require players to check their moves on a video display and interact by using pointing devices such as a mouse. Hence, they are not suitable for visually impaired people. The present paper discusses a multipurpose system that allows especially blind and deafblind people playing chess or other board games over a network, therefore reducing their disability barrier. We describe and benchmark a prototype of a special interactive haptic device for online gaming providing a dual tactile feedback. The novel interface of this proposed device is able to guarantee not only a better game experience for everyone but also an improved quality of life for sight-impaired people.

Access point selection game with mobile users using correlated equilibrium.

PubMed

Sohn, Insoo

2015-01-01

One of the most important issues in wireless local area network (WLAN) systems with multiple access points (APs) is the AP selection problem. Game theory is a mathematical tool used to analyze the interactions in multiplayer systems and has been applied to various problems in wireless networks. Correlated equilibrium (CE) is one of the powerful game theory solution concepts, which is more general than the Nash equilibrium for analyzing the interactions in multiplayer mixed strategy games. A game-theoretic formulation of the AP selection problem with mobile users is presented using a novel scheme based on a regret-based learning procedure. Through convergence analysis, we show that the joint actions based on the proposed algorithm achieve CE. Simulation results illustrate that the proposed algorithm is effective in a realistic WLAN environment with user mobility and achieves maximum system throughput based on the game-theoretic formulation.

Access Point Selection Game with Mobile Users Using Correlated Equilibrium

PubMed Central

Sohn, Insoo

2015-01-01

One of the most important issues in wireless local area network (WLAN) systems with multiple access points (APs) is the AP selection problem. Game theory is a mathematical tool used to analyze the interactions in multiplayer systems and has been applied to various problems in wireless networks. Correlated equilibrium (CE) is one of the powerful game theory solution concepts, which is more general than the Nash equilibrium for analyzing the interactions in multiplayer mixed strategy games. A game-theoretic formulation of the AP selection problem with mobile users is presented using a novel scheme based on a regret-based learning procedure. Through convergence analysis, we show that the joint actions based on the proposed algorithm achieve CE. Simulation results illustrate that the proposed algorithm is effective in a realistic WLAN environment with user mobility and achieves maximum system throughput based on the game-theoretic formulation. PMID:25785726

Collaborative Strategic Board Games as a Site for Distributed Computational Thinking

ERIC Educational Resources Information Center

Berland, Matthew; Lee, Victor R.

2011-01-01

This paper examines the idea that contemporary strategic board games represent an informal, interactional context in which complex computational thinking takes place. When games are collaborative--that is, a game requires that players work in joint pursuit of a shared goal--the computational thinking is easily observed as distributed across…

Topology-dependent rationality and quantal response equilibria in structured populations

NASA Astrophysics Data System (ADS)

Roman, Sabin; Brede, Markus

2017-05-01

Given that the assumption of perfect rationality is rarely met in the real world, we explore a graded notion of rationality in socioecological systems of networked actors. We parametrize an actors' rationality via their place in a social network and quantify system rationality via the average Jensen-Shannon divergence between the games Nash and logit quantal response equilibria. Previous work has argued that scale-free topologies maximize a system's overall rationality in this setup. Here we show that while, for certain games, it is true that increasing degree heterogeneity of complex networks enhances rationality, rationality-optimal configurations are not scale-free. For the Prisoner's Dilemma and Stag Hunt games, we provide analytic arguments complemented by numerical optimization experiments to demonstrate that core-periphery networks composed of a few dominant hub nodes surrounded by a periphery of very low degree nodes give strikingly smaller overall deviations from rationality than scale-free networks. Similarly, for the Battle of the Sexes and the Matching Pennies games, we find that the optimal network structure is also a core-periphery graph but with a smaller difference in the average degrees of the core and the periphery. These results provide insight on the interplay between the topological structure of socioecological systems and their collective cognitive behavior, with potential applications to understanding wealth inequality and the structural features of the network of global corporate control.

Topology-dependent rationality and quantal response equilibria in structured populations.

PubMed

Roman, Sabin; Brede, Markus

2017-05-01

Given that the assumption of perfect rationality is rarely met in the real world, we explore a graded notion of rationality in socioecological systems of networked actors. We parametrize an actors' rationality via their place in a social network and quantify system rationality via the average Jensen-Shannon divergence between the games Nash and logit quantal response equilibria. Previous work has argued that scale-free topologies maximize a system's overall rationality in this setup. Here we show that while, for certain games, it is true that increasing degree heterogeneity of complex networks enhances rationality, rationality-optimal configurations are not scale-free. For the Prisoner's Dilemma and Stag Hunt games, we provide analytic arguments complemented by numerical optimization experiments to demonstrate that core-periphery networks composed of a few dominant hub nodes surrounded by a periphery of very low degree nodes give strikingly smaller overall deviations from rationality than scale-free networks. Similarly, for the Battle of the Sexes and the Matching Pennies games, we find that the optimal network structure is also a core-periphery graph but with a smaller difference in the average degrees of the core and the periphery. These results provide insight on the interplay between the topological structure of socioecological systems and their collective cognitive behavior, with potential applications to understanding wealth inequality and the structural features of the network of global corporate control.

Internet gaming disorder, social network disorder and laterality: handedness relates to pathological use of social networks.

PubMed

Bouna-Pyrrou, Polyxeni; Mühle, Christiane; Kornhuber, Johannes; Lenz, Bernd

2015-08-01

The internet age bears new challenges that include health risks. It is agreed that excessive internet use may reach pathological levels. However, the concept of internet addiction lacks specificity and, therefore, warrants studies on its diagnostic and etiologic classification. This study was conducted to characterize the novel DSM-5 criteria for internet gaming disorder and the adapted criteria for the "social network disorder". Based on the established association of handedness and substance use disorders, we also explored whether internet use related to laterality. For this study, 3,287 volunteers participated in the online survey and gave particulars concerning their internet use in general, internet gaming and use of social networks, laterality markers (hand, foot, eye, ear, rotational preference in gymnastics, and head turning asymmetry) and health status. Of the participants, 1.1 % fulfilled the criteria for internet gaming disorder, and 1.8 % fulfilled the criteria for social network disorder. The applied criteria were highly correlated with the time spent on the respective internet activities (p < 4 × 10(-56)). The analyses of comorbidity and working hours support the thresholds of 5/9 criteria and ≥30 h/week spent on the internet for the classification as pathological (p < 5 × 10(-2)). Moreover, we found that left-handedness related to more affirmed criteria and longer times spent on social networks (p ≤ 4 × 10(-2)). The provided criteria proved to be user-friendly, comprehensible and well accepted. The results contribute to a better understanding of pathological internet gaming and social network use and provide evidence that biological markers of substance use disorders are involved in internet addiction.

GTRF: a game theory approach for regulating node behavior in real-time wireless sensor networks.

PubMed

Lin, Chi; Wu, Guowei; Pirozmand, Poria

2015-06-04

The selfish behaviors of nodes (or selfish nodes) cause packet loss, network congestion or even void regions in real-time wireless sensor networks, which greatly decrease the network performance. Previous methods have focused on detecting selfish nodes or avoiding selfish behavior, but little attention has been paid to regulating selfish behavior. In this paper, a Game Theory-based Real-time & Fault-tolerant (GTRF) routing protocol is proposed. GTRF is composed of two stages. In the first stage, a game theory model named VA is developed to regulate nodes' behaviors and meanwhile balance energy cost. In the second stage, a jumping transmission method is adopted, which ensures that real-time packets can be successfully delivered to the sink before a specific deadline. We prove that GTRF theoretically meets real-time requirements with low energy cost. Finally, extensive simulations are conducted to demonstrate the performance of our scheme. Simulation results show that GTRF not only balances the energy cost of the network, but also prolongs network lifetime.

At the Intersection of Networks and Highly Interactive Online Games

NASA Astrophysics Data System (ADS)

Armitage, Grenville

The game industry continues to evolves its techniques for extracting the most realistic 'immersion' experience for players given the vagaries on best-effort Internet service. A key challenge for service providers is understanding the characteristics of traffic imposed on networks by games, and their service quality requirements. Interactive online games are particularly susceptible to the side effects of other non-interactive (or delay- and loss-tolerant) traffic sharing next- generation access links. This creates challenges out toward the edges, where high-speed home LANs squeeze through broadband consumer access links to reach the Internet. In this chapter we identify a range of research work exploring many issues associated with the intersection of highly interactive games and the Internet, and hopefully stimulate some further thinking along these lines.

Spatial prisoner's dilemma game with volunteering in Newman-Watts small-world networks

NASA Astrophysics Data System (ADS)

Wu, Zhi-Xi; Xu, Xin-Jian; Chen, Yong; Wang, Ying-Hai

2005-03-01

A modified spatial prisoner’s dilemma game with voluntary participation in Newman-Watts small-world networks is studied. Some reasonable ingredients are introduced to the game evolutionary dynamics: each agent in the network is a pure strategist and can only take one of three strategies (cooperator, defector, and loner); its strategical transformation is associated with both the number of strategical states and the magnitude of average profits, which are adopted and acquired by its coplayers in the previous round of play; a stochastic strategy mutation is applied when it gets into the trouble of local commons that the agent and its neighbors are in the same state and get the same average payoffs. In the case of very low temptation to defect, it is found that agents are willing to participate in the game in typical small-world region and intensive collective oscillations arise in more random region.

Extensive video-game experience alters cortical networks for complex visuomotor transformations.

PubMed

Granek, Joshua A; Gorbet, Diana J; Sergio, Lauren E

2010-10-01

Using event-related functional magnetic resonance imaging (fMRI), we examined the effect of video-game experience on the neural control of increasingly complex visuomotor tasks. Previously, skilled individuals have demonstrated the use of a more efficient movement control brain network, including the prefrontal, premotor, primary sensorimotor and parietal cortices. Our results extend and generalize this finding by documenting additional prefrontal cortex activity in experienced video gamers planning for complex eye-hand coordination tasks that are distinct from actual video-game play. These changes in activation between non-gamers and extensive gamers are putatively related to the increased online control and spatial attention required for complex visually guided reaching. These data suggest that the basic cortical network for processing complex visually guided reaching is altered by extensive video-game play. Crown Copyright © 2009. Published by Elsevier Srl. All rights reserved.

Developing and Assessing Teachers' Knowledge of Game-Based Learning

ERIC Educational Resources Information Center

Shah, Mamta; Foster, Aroutis

2015-01-01

Research focusing on the development and assessment of teacher knowledge in game-based learning is in its infancy. A mixed-methods study was undertaken to educate pre-service teachers in game-based learning using the Game Network Analysis (GaNA) framework. Fourteen pre-service teachers completed a methods course, which prepared them in game…

Efficient Allocation of Resources for Defense of Spatially Distributed Networks Using Agent-Based Simulation.

PubMed

Kroshl, William M; Sarkani, Shahram; Mazzuchi, Thomas A

2015-09-01

This article presents ongoing research that focuses on efficient allocation of defense resources to minimize the damage inflicted on a spatially distributed physical network such as a pipeline, water system, or power distribution system from an attack by an active adversary, recognizing the fundamental difference between preparing for natural disasters such as hurricanes, earthquakes, or even accidental systems failures and the problem of allocating resources to defend against an opponent who is aware of, and anticipating, the defender's efforts to mitigate the threat. Our approach is to utilize a combination of integer programming and agent-based modeling to allocate the defensive resources. We conceptualize the problem as a Stackelberg "leader follower" game where the defender first places his assets to defend key areas of the network, and the attacker then seeks to inflict the maximum damage possible within the constraints of resources and network structure. The criticality of arcs in the network is estimated by a deterministic network interdiction formulation, which then informs an evolutionary agent-based simulation. The evolutionary agent-based simulation is used to determine the allocation of resources for attackers and defenders that results in evolutionary stable strategies, where actions by either side alone cannot increase its share of victories. We demonstrate these techniques on an example network, comparing the evolutionary agent-based results to a more traditional, probabilistic risk analysis (PRA) approach. Our results show that the agent-based approach results in a greater percentage of defender victories than does the PRA-based approach. © 2015 Society for Risk Analysis.

Is the Internet gaming-addicted brain close to be in a pathological state?

PubMed

Park, Chang-Hyun; Chun, Ji-Won; Cho, Huyn; Jung, Young-Chul; Choi, Jihye; Kim, Dai Jin

2017-01-01

Internet gaming addiction (IGA) is becoming a common and widespread mental health concern. Although IGA induces a variety of negative psychosocial consequences, it is yet ambiguous whether the brain addicted to Internet gaming is considered to be in a pathological state. We investigated IGA-induced abnormalities of the brain specifically from the network perspective and qualitatively assessed whether the Internet gaming-addicted brain is in a state similar to the pathological brain. Topological properties of brain functional networks were examined by applying a graph-theoretical approach to analyzing functional magnetic resonance imaging data acquired during a resting state in 19 IGA adolescents and 20 age-matched healthy controls. We compared functional distance-based measures, global and local efficiency of resting state brain functional networks between the two groups to assess how the IGA subjects' brain was topologically altered from the controls' brain. The IGA subjects had severer impulsiveness and their brain functional networks showed higher global efficiency and lower local efficiency relative to the controls. These topological differences suggest that IGA induced brain functional networks to shift toward the random topological architecture, as exhibited in other pathological states. Furthermore, for the IGA subjects, the topological alterations were specifically attributable to interregional connections incident on the frontal region, and the degree of impulsiveness was associated with the topological alterations over the frontolimbic connections. The current findings lend support to the proposition that the Internet gaming-addicted brain could be in the state similar to pathological states in terms of topological characteristics of brain functional networks. © 2015 Society for the Study of Addiction.

A Game Theory Based Solution for Security Challenges in CRNs

NASA Astrophysics Data System (ADS)

Poonam; Nagpal, Chander Kumar

2018-03-01

Cognitive radio networks (CRNs) are being envisioned to drive the next generation Ad hoc wireless networks due to their ability to provide communications resilience in continuously changing environments through the use of dynamic spectrum access. Conventionally CRNs are dependent upon the information gathered by other secondary users to ensure the accuracy of spectrum sensing making them vulnerable to security attacks leading to the need of security mechanisms like cryptography and trust. However, a typical cryptography based solution is not a viable security solution for CRNs owing to their limited resources. Effectiveness of trust based approaches has always been, in question, due to credibility of secondary trust resources. Game theory with its ability to optimize in an environment of conflicting interests can be quite a suitable tool to manage an ad hoc network in the presence of autonomous selfish/malevolent/malicious and attacker nodes. The literature contains several theoretical proposals for augmenting game theory in the ad hoc networks without explicit/detailed implementation. This paper implements a game theory based solution in MATLAB-2015 to secure the CRN environment and compares the obtained results with the traditional approaches of trust and cryptography. The simulation result indicates that as the time progresses the game theory performs much better with higher throughput, lower jitter and better identification of selfish/malicious nodes.

Equilibria, information and frustration in heterogeneous network games with conflicting preferences

NASA Astrophysics Data System (ADS)

Mazzoli, M.; Sánchez, A.

2017-11-01

Interactions between people are the basis on which the structure of our society arises as a complex system and, at the same time, are the starting point of any physical description of it. In the last few years, much theoretical research has addressed this issue by combining the physics of complex networks with a description of interactions in terms of evolutionary game theory. We here take this research a step further by introducing a most salient societal factor such as the individuals’ preferences, a characteristic that is key to understanding much of the social phenomenology these days. We consider a heterogeneous, agent-based model in which agents interact strategically with their neighbors, but their preferences and payoffs for the possible actions differ. We study how such a heterogeneous network behaves under evolutionary dynamics and different strategic interactions, namely coordination games and best shot games. With this model we study the emergence of the equilibria predicted analytically in random graphs under best response dynamics, and we extend this test to unexplored contexts like proportional imitation and scale free networks. We show that some theoretically predicted equilibria do not arise in simulations with incomplete information, and we demonstrate the importance of the graph topology and the payoff function parameters for some games. Finally, we discuss our results with the available experimental evidence on coordination games, showing that our model agrees better with the experiment than standard economic theories, and draw hints as to how to maximize social efficiency in situations of conflicting preferences.

Coevolving agent strategies and network topology for the public goods games

NASA Astrophysics Data System (ADS)

Zhang, C. Y.; Zhang, J. L.; Xie, G. M.; Wang, L.

2011-03-01

Much of human cooperation remains an evolutionary riddle. Coevolutionary public goods games in structured populations are studied where players can change from an unproductive public goods game to a productive one, by evaluating the productivity of the public goods games. In our model, each individual participates in games organized by its neighborhood plus by itself. Coevolution here refers to an evolutionary process entailing both deletion of existing links and addition of new links between agents that accompanies the evolution of their strategies. Furthermore, we investigate the effects of time scale separation of strategy and structure on cooperation level. This study presents the following: Foremost, we observe that high cooperation levels in public goods interactions are attained by the entangled coevolution of strategy and structure. Presented results also confirm that the resulting networks show many features of real systems, such as cooperative behavior and hierarchical clustering. The heterogeneity of the interaction network is held responsible for the observed promotion of cooperation. We hope our work may offer an explanation for the origin of large-scale cooperative behavior among unrelated individuals.

Gamification and serious games for personalized health.

PubMed

McCallum, Simon

2012-01-01

Computer games are no longer just a trivial activity played by children in arcades. Social networking and casual gaming have broadened the market for, and acceptance of, games. This has coincided with a realization of their power to engage and motivate players. Good computer games are excellent examples of modern educational theory [1]. The military, health providers, governments, and educators, all use computer games. This paper focuses on Games for Health, discussing the range of areas and approaches to developing these games. We extend a taxonomy for Games for Health, describe a case study on games for dementia sufferers, and finally, present some challenges and research opportunities in this area.

Markets on Networks

NASA Astrophysics Data System (ADS)

Toroczkai, Zoltan; Anghel, Marian; Bassler, Kevin; Korniss, Gyorgy

2003-03-01

The dynamics of human, and most biological populations is characterized by competition for resources. By its own nature, this dynamics creates the group of "elites", formed by those agents who have strategies that are the most successful in the given situation, and therefore the rest of the agents will tend to follow, imitate, or interact with them, creating a social structure of leadership in the agent society. These inter-agent communications generate a complex social network with small-world character which itself forms the substrate for a second network, the action network. The latter is a highly dynamic, adaptive, directed network, defined by those inter-agent communication links on the substrate along which the passed information /prediction is acted upon by the other agents. By using the minority game for competition dynamics, here we show that when the substrate network is highly connected, the action network spontaneously develops hubs with a broad distribution of out-degrees, defining a robust leadership structure that is scale-free. Furthermore, in certain, realistic parameter ranges, facilitated by information passing on the action network, agents can spontaneously generate a high degree of cooperation making the collective almost maximally efficient.

Group-based strategy diffusion in multiplex networks with weighted values

NASA Astrophysics Data System (ADS)

Yu, Jianyong; Jiang, J. C.; Xiang, Leijun

2017-03-01

The information diffusion of multiplex social networks has received increasing interests in recent years. Actually, the multiplex networks are made of many communities, and it should be gotten more attention for the influences of community level diffusion, besides of individual level interactions. In view of this, this work explores strategy interactions and diffusion processes in multiplex networks with weighted values from a new perspective. Two different groups consisting of some agents with different influential strength are firstly built in each layer network, the authority and non-authority groups. The strategy interactions between different groups in intralayer and interlayer networks are performed to explore community level diffusion, by playing two classical strategy games, Prisoner's Dilemma and Snowdrift Game. The impact forces from the different groups and the reactive forces from individual agents are simultaneously taken into account in intralayer and interlayer interactions. This paper reveals and explains the evolutions of cooperation diffusion and the influences of interlayer interaction tight degrees in multiplex networks with weighted values. Some thresholds of critical parameters of interaction degrees and games parameters settings are also discussed in group-based strategy diffusion.

Component Neural Systems for the Creation of Emotional Memories during Free Viewing of a Complex, Real-World Event

PubMed Central

Botzung, Anne; LaBar, Kevin S.; Kragel, Philip; Miles, Amanda; Rubin, David C.

2010-01-01

To investigate the neural systems that contribute to the formation of complex, self-relevant emotional memories, dedicated fans of rival college basketball teams watched a competitive game while undergoing functional magnetic resonance imaging (fMRI). During a subsequent recognition memory task, participants were shown video clips depicting plays of the game, stemming either from previously-viewed game segments (targets) or from non-viewed portions of the same game (foils). After an old–new judgment, participants provided emotional valence and intensity ratings of the clips. A data driven approach was first used to decompose the fMRI signal acquired during free viewing of the game into spatially independent components. Correlations were then calculated between the identified components and post-scanning emotion ratings for successfully encoded targets. Two components were correlated with intensity ratings, including temporal lobe regions implicated in memory and emotional functions, such as the hippocampus and amygdala, as well as a midline fronto-cingulo-parietal network implicated in social cognition and self-relevant processing. These data were supported by a general linear model analysis, which revealed additional valence effects in fronto-striatal-insular regions when plays were divided into positive and negative events according to the fan's perspective. Overall, these findings contribute to our understanding of how emotional factors impact distributed neural systems to successfully encode dynamic, personally-relevant event sequences. PMID:20508750

Efficient data communication protocols for wireless networks

NASA Astrophysics Data System (ADS)

Zeydan, Engin

In this dissertation, efficient decentralized algorithms are investigated for cost minimization problems in wireless networks. For wireless sensor networks, we investigate both the reduction in the energy consumption and throughput maximization problems separately using multi-hop data aggregation for correlated data in wireless sensor networks. The proposed algorithms exploit data redundancy using a game theoretic framework. For energy minimization, routes are chosen to minimize the total energy expended by the network using best response dynamics to local data. The cost function used in routing takes into account distance, interference and in-network data aggregation. The proposed energy-efficient correlation-aware routing algorithm significantly reduces the energy consumption in the network and converges in a finite number of steps iteratively. For throughput maximization, we consider both the interference distribution across the network and correlation between forwarded data when establishing routes. Nodes along each route are chosen to minimize the interference impact in their neighborhood and to maximize the in-network data aggregation. The resulting network topology maximizes the global network throughput and the algorithm is guaranteed to converge with a finite number of steps using best response dynamics. For multiple antenna wireless ad-hoc networks, we present distributed cooperative and regret-matching based learning schemes for joint transmit beanformer and power level selection problem for nodes operating in multi-user interference environment. Total network transmit power is minimized while ensuring a constant received signal-to-interference and noise ratio at each receiver. In cooperative and regret-matching based power minimization algorithms, transmit beanformers are selected from a predefined codebook to minimize the total power. By selecting transmit beamformers judiciously and performing power adaptation, the cooperative algorithm is shown to converge to pure strategy Nash equilibrium with high probability throughout the iterations in the interference impaired network. On the other hand, the regret-matching learning algorithm is noncooperative and requires minimum amount of overhead. The proposed cooperative and regret-matching based distributed algorithms are also compared with centralized solutions through simulation results.

Effects of Network Characteristics on Reaching the Payoff-Dominant Equilibrium in Coordination Games: A Simulation study.

PubMed

Buskens, Vincent; Snijders, Chris

2016-01-01

We study how payoffs and network structure affect reaching the payoff-dominant equilibrium in a [Formula: see text] coordination game that actors play with their neighbors in a network. Using an extensive simulation analysis of over 100,000 networks with 2-25 actors, we show that the importance of network characteristics is restricted to a limited part of the payoff space. In this part, we conclude that the payoff-dominant equilibrium is chosen more often if network density is larger, the network is more centralized, and segmentation of the network is smaller. Moreover, it is more likely that heterogeneity in behavior persists if the network is more segmented and less centralized. Persistence of heterogeneous behavior is not related to network density.

The Use of Massive Multiplayer Online Games to Evaluate C4I Systems

DTIC Science & Technology

2004-03-01

popularity in the gaming industry , the public and the Department of Defense. Improvements to computer technology and the increased data transfer rate...Multiplayer Online Games (MMOG) have gained in popularity in the gaming industry , the public and the Department of Defense. Improvements to...have gained in popularity in the gaming industry , the public and the Department of Defense. These networked virtual environments are “a software

The Girl Game Company: Engaging Latina Girls in Information Technology

ERIC Educational Resources Information Center

Denner, Jill; Bean, Steve; Martinez, Jacob

2009-01-01

This article describes the Girl Game Company's involvement in teaching Latina girls to design and program computer games while building a network of support to help them pursue IT courses and careers. Afterschool programs like the Girl Game Company can fill an important gap by providing opportunities for underserved youth to build IT fluency. A…

The Application of Cognitive Diagnostic Approaches via Neural Network Analysis of Serious Educational Games

ERIC Educational Resources Information Center

Lamb, Richard L.

2013-01-01

Serious Educational Games (SEGs) have been a topic of increased popularity within the educational realm since the early millennia. SEGs are generalized form of Serious Games to mean games for purposes other than entertainment but, that also specifically include training, educational purpose and pedagogy within their design. This rise in popularity…

Dynamical origins of the community structure of an online multi-layer society

NASA Astrophysics Data System (ADS)

Klimek, Peter; Diakonova, Marina; Eguíluz, Víctor M.; San Miguel, Maxi; Thurner, Stefan

2016-08-01

Social structures emerge as a result of individuals managing a variety of different social relationships. Societies can be represented as highly structured dynamic multiplex networks. Here we study the dynamical origins of the specific community structures of a large-scale social multiplex network of a human society that interacts in a virtual world of a massive multiplayer online game. There we find substantial differences in the community structures of different social actions, represented by the various layers in the multiplex network. Community sizes distributions are either fat-tailed or appear to be centered around a size of 50 individuals. To understand these observations we propose a voter model that is built around the principle of triadic closure. It explicitly models the co-evolution of node- and link-dynamics across different layers of the multiplex network. Depending on link and node fluctuation probabilities, the model exhibits an anomalous shattered fragmentation transition, where one layer fragments from one large component into many small components. The observed community size distributions are in good agreement with the predicted fragmentation in the model. This suggests that several detailed features of the fragmentation in societies can be traced back to the triadic closure processes.

Electromagnetic game modeling through Tensor Analysis of Networks and Game Theory

NASA Astrophysics Data System (ADS)

Maurice, Olivier; Reineix, Alain; Lalléchère, Sébastien

2014-10-01

A complex system involves events coming from natural behaviors. Whatever is the complicated face of machines, they are still far from the complexity of natural systems. Currently, economy is one of the rare science trying to find out some ways to model human behavior. These attempts involve game theory and psychology. Our purpose is to develop a formalism able to take in charge both game and hardware modeling. We first present the Tensorial Analysis of Networks, used for the material part of the system. Then, we detail the mathematical objects defined in order to describe the evolution of the system and its gaming side. To illustrate the discussion we consider the case of a drone whose electronic can be disturbed by a radar field, but this drone must fly as near as possible close to this radar.

Bribery games on inter-dependent regular networks

NASA Astrophysics Data System (ADS)

Verma, Prateek; Nandi, Anjan K.; Sengupta, Supratim

2017-02-01

We examine a scenario of social conflict that is manifest during an interaction between government servants providing a service and citizens who are legally entitled to the service, using evolutionary game-theory in structured populations characterized by an inter-dependent network. Bribe-demands by government servants during such transactions, called harassment bribes, constitute a widespread form of corruption in many countries. We investigate the effect of varying bribe demand made by corrupt officials and the cost of complaining incurred by harassed citizens, on the proliferation of corrupt strategies in the population. We also examine how the connectivity of the various constituent networks affects the spread of corrupt officials in the population. We find that incidents of bribery can be considerably reduced in a network-structured populations compared to mixed populations. Interestingly, we also find that an optimal range for the connectivity of nodes in the citizen’s network (signifying the degree of influence a citizen has in affecting the strategy of other citizens in the network) as well as the interaction network aids in the fixation of honest officers. Our results reveal the important role of network structure and connectivity in asymmetric games.

Bribery games on inter-dependent regular networks

PubMed Central

Verma, Prateek; Nandi, Anjan K.; Sengupta, Supratim

2017-01-01

We examine a scenario of social conflict that is manifest during an interaction between government servants providing a service and citizens who are legally entitled to the service, using evolutionary game-theory in structured populations characterized by an inter-dependent network. Bribe-demands by government servants during such transactions, called harassment bribes, constitute a widespread form of corruption in many countries. We investigate the effect of varying bribe demand made by corrupt officials and the cost of complaining incurred by harassed citizens, on the proliferation of corrupt strategies in the population. We also examine how the connectivity of the various constituent networks affects the spread of corrupt officials in the population. We find that incidents of bribery can be considerably reduced in a network-structured populations compared to mixed populations. Interestingly, we also find that an optimal range for the connectivity of nodes in the citizen’s network (signifying the degree of influence a citizen has in affecting the strategy of other citizens in the network) as well as the interaction network aids in the fixation of honest officers. Our results reveal the important role of network structure and connectivity in asymmetric games. PMID:28205644

Remote gaming on resource-constrained devices

NASA Astrophysics Data System (ADS)

Reza, Waazim; Kalva, Hari; Kaufman, Richard

2010-08-01

Games have become important applications on mobile devices. A mobile gaming approach known as remote gaming is being developed to support games on low cost mobile devices. In the remote gaming approach, the responsibility of rendering a game and advancing the game play is put on remote servers instead of the resource constrained mobile devices. The games rendered on the servers are encoded as video and streamed to mobile devices. Mobile devices gather user input and stream the commands back to the servers to advance game play. With this solution, mobile devices with video playback and network connectivity can become game consoles. In this paper we present the design and development of such a system and evaluate the performance and design considerations to maximize the end user gaming experience.

Exact probability distribution functions for Parrondo's games

NASA Astrophysics Data System (ADS)

Zadourian, Rubina; Saakian, David B.; Klümper, Andreas

2016-12-01

We study the discrete time dynamics of Brownian ratchet models and Parrondo's games. Using the Fourier transform, we calculate the exact probability distribution functions for both the capital dependent and history dependent Parrondo's games. In certain cases we find strong oscillations near the maximum of the probability distribution with two limiting distributions for odd and even number of rounds of the game. Indications of such oscillations first appeared in the analysis of real financial data, but now we have found this phenomenon in model systems and a theoretical understanding of the phenomenon. The method of our work can be applied to Brownian ratchets, molecular motors, and portfolio optimization.

Exact probability distribution functions for Parrondo's games.

PubMed

Zadourian, Rubina; Saakian, David B; Klümper, Andreas

2016-12-01

We study the discrete time dynamics of Brownian ratchet models and Parrondo's games. Using the Fourier transform, we calculate the exact probability distribution functions for both the capital dependent and history dependent Parrondo's games. In certain cases we find strong oscillations near the maximum of the probability distribution with two limiting distributions for odd and even number of rounds of the game. Indications of such oscillations first appeared in the analysis of real financial data, but now we have found this phenomenon in model systems and a theoretical understanding of the phenomenon. The method of our work can be applied to Brownian ratchets, molecular motors, and portfolio optimization.

Evolutionary Artificial Neural Network Weight Tuning to Optimize Decision Making for an Abstract Game

DTIC Science & Technology

2010-03-01

separate LoA heuristic. If any of the examined heuristics produced competitive player , then the final measurement was a success . Barring that, a...if offline training actually results in a successful player . Whereas offline learning plays many games and then trains as many networks as desired...a competitive Lines of Action player , shedding light on the difficulty of developing a neural network to model such a large and complex solution

The design of the m-health service application using a Nintendo DS game console.

PubMed

Lee, Sangjoon; Kim, Jungkuk; Lee, Myoungho

2011-03-01

In this article, we developed an m-health monitoring system using a Nintendo DS game console to demonstrate its utility. The proposed system consists of a biosignal acquisition device, wireless sensor network, base-station for signal reception from the sensor network and signal conversion according to Internet protocol, personal computer display program, and the Nintendo DS game console. The system collects three-channel electrocardiogram (ECG) signals for cardiac abnormality detection and three-axis accelerometer signals for fall detection of a person. The collected signals are then transmitted to the base-station through the wireless sensor network, where they are transformed according to the transmission control protocol/Internet protocol (TCP/IP) and sent to the destination IP through Internet network. To test the developed system, the collected signals were displayed on a computer located in different building through wired Internet network and also simultaneously displayed on the Nintendo DS game console connected to Internet network wirelessly. The system was able to collect and transmit signals for more than 24 h without any interruptions or malfunctions, showing the possibility of integrating healthcare monitoring functions into a small handheld-type electronic device developed for different purposes without significant complications. It is expected that the system can be used in an ambulance, nursing home, or general hospital where efficient patient monitoring from long distance is necessary.

Exploring Classroom Community: A Social Network Study of Reacting to the Past

ERIC Educational Resources Information Center

Webb, Jeff; Engar, Ann

2016-01-01

In this exploratory social network study, we examined how student relationships evolved during three month-long Reacting to the Past (RTTP) role-playing games in a lower division honors course at a large US public university. Our purpose was to explore how RTTP games--and collaborative learning approaches more generally--impact classroom community…

Enhancing Formal E-Learning with Edutainment on Social Networks

ERIC Educational Resources Information Center

Labus, A.; Despotovic-Zrakic, M.; Radenkovic, B.; Bogdanovic, Z.; Radenkovic, M.

2015-01-01

This paper reports on the investigation of the possibilities of enhancing the formal e-learning process by harnessing the potential of informal game-based learning on social networks. The goal of the research is to improve the outcomes of the formal learning process through the design and implementation of an educational game on a social network…

Constant Price of Anarchy in Network Creation Games via Public Service Advertising

NASA Astrophysics Data System (ADS)

Demaine, Erik D.; Zadimoghaddam, Morteza

Network creation games have been studied in many different settings recently. These games are motivated by social networks in which selfish agents want to construct a connection graph among themselves. Each node wants to minimize its average or maximum distance to the others, without paying much to construct the network. Many generalizations have been considered, including non-uniform interests between nodes, general graphs of allowable edges, bounded budget agents, etc. In all of these settings, there is no known constant bound on the price of anarchy. In fact, in many cases, the price of anarchy can be very large, namely, a constant power of the number of agents. This means that we have no control on the behavior of network when agents act selfishly. On the other hand, the price of stability in all these models is constant, which means that there is chance that agents act selfishly and we end up with a reasonable social cost.

Competition among networks highlights the power of the weak

PubMed Central

Iranzo, Jaime; Buldú, Javier M.; Aguirre, Jacobo

2016-01-01

The unpreventable connections between real networked systems have recently called for an examination of percolation, diffusion or synchronization phenomena in multilayer networks. Here we use network science and game theory to explore interactions in networks-of-networks and model these as a game for gaining importance. We propose a viewpoint where networks choose the connection strategies, in contrast with classical approaches where nodes are the active players. Specifically, we investigate how creating paths between networks leads to different Nash equilibria that determine their structural and dynamical properties. In a wide variety of cases, selecting adequate connections leads to a cooperative solution that allows weak networks to overcome the strongest opponent. Counterintuitively, each weak network can induce a global transition to such cooperative configuration regardless of the actions of the strongest network. This power of the weak reveals a critical dominance of the underdogs in the fate of networks-of-networks. PMID:27841258

Simulation and Gaming: Directions, Issues, Ponderables.

ERIC Educational Resources Information Center

Uretsky, Michael

1995-01-01

Discusses the current use of simulation and gaming in a variety of settings. Describes advances in technology that facilitate the use of simulation and gaming, including computer power, computer networks, software, object-oriented programming, video, multimedia, virtual reality, and artificial intelligence. Considers the future use of simulation…

[The effects of narcissism and self-esteem on immersion in social network games and massively multiplayer online role-playing games].

PubMed

Jin, Kato; Igarashi, Tasuku

2016-04-01

Recent research has shown growing interest in the process by which narcissism triggers immersion in social network games (SNG). Highly narcissistic individuals are motivated not only by the achievement of goals and monopoly of materials (i:e., self-enhancement), but also by comparison and competition with others (i.e., social comparison) We predicted that the common rules and environments of SNG and massively multiplayer online role-playing games (MMORPG), such as systems of exchanging items and ranking players, facilitate immersion of highly narcissistic individuals during the game. Structural equation modeling of data from 378 SNG players and 150 MMORPG players recruited online showed that self-esteem inhibited game immersion, whereas narcissism increased game immersion via motivation for goal attainment. SNG players were more likely to be immersed in the game via motivation for goal attainment than MMORPG players. These findings suggest that, compared with MMORPG, the environments of SNG provide strong incentives not for those high in self-esteem who seek acceptance of others, but for those high in narcissism who are motivated by self-enhancement via competition with others.

A Simple Game to Derive Lognormal Distribution

ERIC Educational Resources Information Center

Omey, E.; Van Gulck, S.

2007-01-01

In the paper we present a simple game that students can play in the classroom. The game can be used to show that random variables can behave in an unexpected way: the expected mean can tend to zero or to infinity; the variance can tend to zero or to infinity. The game can also be used to introduce the lognormal distribution. (Contains 1 table and…

Analysis of context dependence in social interaction networks of a massively multiplayer online role-playing game.

PubMed

Son, Seokshin; Kang, Ah Reum; Kim, Hyun-chul; Kwon, Taekyoung; Park, Juyong; Kim, Huy Kang

2012-01-01

Rapid advances in modern computing and information technology have enabled millions of people to interact online via various social network and gaming services. The widespread adoption of such online services have made possible analysis of large-scale archival data containing detailed human interactions, presenting a very promising opportunity to understand the rich and complex human behavior. In collaboration with a leading global provider of Massively Multiplayer Online Role-Playing Games (MMORPGs), here we present a network science-based analysis of the interplay between distinct types of user interaction networks in the virtual world. We find that their properties depend critically on the nature of the context-interdependence of the interactions, highlighting the complex and multilayered nature of human interactions, a robust understanding of which we believe may prove instrumental in the designing of more realistic future virtual arenas as well as provide novel insights to the science of collective human behavior.

A novel game theoretic approach for modeling competitive information diffusion in social networks with heterogeneous nodes

NASA Astrophysics Data System (ADS)

Agha Mohammad Ali Kermani, Mehrdad; Fatemi Ardestani, Seyed Farshad; Aliahmadi, Alireza; Barzinpour, Farnaz

2017-01-01

Influence maximization deals with identification of the most influential nodes in a social network given an influence model. In this paper, a game theoretic framework is developed that models a competitive influence maximization problem. A novel competitive influence model is additionally proposed that incorporates user heterogeneity, message content, and network structure. The proposed game-theoretic model is solved using Nash Equilibrium in a real-world dataset. It is shown that none of the well-known strategies are stable and at least one player has the incentive to deviate from the proposed strategy. Moreover, violation of Nash equilibrium strategy by each player leads to their reduced payoff. Contrary to previous works, our results demonstrate that graph topology, as well as the nodes' sociability and initial tendency measures have an effect on the determination of the influential node in the network.

Fair and efficient network congestion control based on minority game

NASA Astrophysics Data System (ADS)

Wang, Zuxi; Wang, Wen; Hu, Hanping; Deng, Zhaozhang

2011-12-01

Low link utility, RTT unfairness and unfairness of Multi-Bottleneck network are the existing problems in the present network congestion control algorithms at large. Through the analogy of network congestion control with the "El Farol Bar" problem, we establish a congestion control model based on minority game(MG), and then present a novel network congestion control algorithm based on the model. The result of simulations indicates that the proposed algorithm can make the achievements of link utility closing to 100%, zero packet lose rate, and small of queue size. Besides, the RTT unfairness and the unfairness of Multi-Bottleneck network can be solved, to achieve the max-min fairness in Multi-Bottleneck network, while efficiently weaken the "ping-pong" oscillation caused by the overall synchronization.

Coevolution of dynamical states and interactions in dynamic networks

NASA Astrophysics Data System (ADS)

Zimmermann, Martín G.; Eguíluz, Víctor M.; San Miguel, Maxi

2004-06-01

We explore the coupled dynamics of the internal states of a set of interacting elements and the network of interactions among them. Interactions are modeled by a spatial game and the network of interaction links evolves adapting to the outcome of the game. As an example, we consider a model of cooperation in which the adaptation is shown to facilitate the formation of a hierarchical interaction network that sustains a highly cooperative stationary state. The resulting network has the characteristics of a small world network when a mechanism of local neighbor selection is introduced in the adaptive network dynamics. The highly connected nodes in the hierarchical structure of the network play a leading role in the stability of the network. Perturbations acting on the state of these special nodes trigger global avalanches leading to complete network reorganization.

Interdependency enriches the spatial reciprocity in prisoner's dilemma game on weighted networks

NASA Astrophysics Data System (ADS)

Meng, Xiaokun; Sun, Shiwen; Li, Xiaoxuan; Wang, Li; Xia, Chengyi; Sun, Junqing

2016-01-01

To model the evolution of cooperation under the realistic scenarios, we propose an interdependent network-based game model which simultaneously considers the difference of individual roles in the spatial prisoner's dilemma game. In our model, the system is composed of two lattices on which an agent designated as a cooperator or defector will be allocated, meanwhile each agent will be endowed as a specific weight taking from three typical distributions on one lattice (i.e., weighted lattice), and set to be 1.0 on the other one (i.e., un-weighted or standard lattice). In addition, the interdependency will be built through the utility coupling between point-to-point partners. Extensive simulations indicate that the cooperation will be continuously elevated for the weighted lattice as the utility coupling strength (α) increases; while the cooperation will take on a nontrivial evolution on the standard lattice as α varies, and will be still greatly promoted when compared to the case of α = 0. At the same time, the full T - K phase diagrams are also explored to illustrate the evolutionary behaviors, and it is powerfully shown that the interdependency drives the defectors to survive within the narrower range, but individual weighting of utility will further broaden the coexistence space of cooperators and defectors, which renders the nontrivial evolution of cooperation in our model. Altogether, the current consequences about the evolution of cooperation will be helpful for us to provide the insights into the prevalent cooperation phenomenon within many real-world systems.

Long-Term Changes in Game Species Over a Long Period of Transformation in the Iberian Mediterranean Landscape

NASA Astrophysics Data System (ADS)

Delibes-Mateos, Miguel; Farfán, Miguel Ángel; Olivero, Jesús; Márquez, Ana Luz; Vargas, Juan Mario

2009-06-01

Agricultural change has transformed large areas of traditional farming landscapes, leading to important changes in the species community assemblages in most European countries. We suspect that the drastic changes in land-use that have occurred in Andalusia (southern Spain) over recent decades, may have affected the distribution and abundance of game species in this region. This article compares the distribution of the main game species in Andalusia during the 1960s and 1990s, using data from maps available from the Mainland Spanish Fish, Game and National Parks Service and from recent datasets on hunting yield distributions, respectively. Big-game and small-game species were significantly segregated in southern Spain during the 1990s, as two clearly independent chorotypes (groups of species whose abundances are similarly distributed) were obtained from the classification analysis. In contrast, big-game and small-game species were not significantly segregated several decades ago, when there was only one chorotype consisting of small-game species and wild boar. The other three ungulates did not constitute a significant chorotype, as they showed positive correlations with some species in the group mentioned above. These changes seem to be a consequence of the transformations that have occurred in the Iberian Mediterranean landscape over the last few decades. The abandoning of traditional activities, and the consequent formation of dense scrubland and woodland, has led to an expansion of big-game species, and a decrease of small-game species in mountain areas. Moreover, agricultural intensification has apparently depleted small-game species populations in some agricultural areas. On the other hand, the increasingly intensive hunting management could be artificially boosting this segregation between small-game and big-game species. Our results suggest that the conservation and regeneration of traditional agricultural landscapes (like those predominating in the 1960s) should be a priority for the conservation of small-game species.

Developing a policy game intervention to enhance collaboration in public health policymaking in three European countries.

PubMed

Spitters, H P E M; van Oers, J A M; Sandu, P; Lau, C J; Quanjel, M; Dulf, D; Chereches, R; van de Goor, L A M

2017-12-19

One of the key elements to enhance the uptake of evidence in public health policies is stimulating cross-sector collaboration. An intervention stimulating collaboration is a policy game. The aim of this study was to describe the design and methods of the development process of the policy game ‘In2Action’ within a real-life setting of public health policymaking networks in the Netherlands, Denmark and Romania. The development of the policy game intervention consisted of three phases, pre intervention, designing the game intervention and tailoring the intervention. In2Action was developed as a role-play game of one day, with main focus to develop in collaboration a cross-sector implementation plan based on the approved strategic local public health policy. This study introduced an innovative intervention for public health policymaking. It described the design and development of the generic frame of the In2Action game focusing on enhancing collaboration in local public health policymaking networks. By keeping the game generic, it became suitable for each of the three country cases with only minor changes. The generic frame of the game is expected to be generalizable for other European countries to stimulate interaction and collaboration in the policy process.

Cascading failures and the emergence of cooperation in evolutionary-game based models of social and economical networks.

PubMed

Wang, Wen-Xu; Lai, Ying-Cheng; Armbruster, Dieter

2011-09-01

We study catastrophic behaviors in large networked systems in the paradigm of evolutionary games by incorporating a realistic "death" or "bankruptcy" mechanism. We find that a cascading bankruptcy process can arise when defection strategies exist and individuals are vulnerable to deficit. Strikingly, we observe that, after the catastrophic cascading process terminates, cooperators are the sole survivors, regardless of the game types and of the connection patterns among individuals as determined by the topology of the underlying network. It is necessary that individuals cooperate with each other to survive the catastrophic failures. Cooperation thus becomes the optimal strategy and absolutely outperforms defection in the game evolution with respect to the "death" mechanism. Our results can be useful for understanding large-scale catastrophe in real-world systems and in particular, they may yield insights into significant social and economical phenomena such as large-scale failures of financial institutions and corporations during an economic recession.

Cascading failures and the emergence of cooperation in evolutionary-game based models of social and economical networks

NASA Astrophysics Data System (ADS)

Wang, Wen-Xu; Lai, Ying-Cheng; Armbruster, Dieter

2011-09-01

We study catastrophic behaviors in large networked systems in the paradigm of evolutionary games by incorporating a realistic "death" or "bankruptcy" mechanism. We find that a cascading bankruptcy process can arise when defection strategies exist and individuals are vulnerable to deficit. Strikingly, we observe that, after the catastrophic cascading process terminates, cooperators are the sole survivors, regardless of the game types and of the connection patterns among individuals as determined by the topology of the underlying network. It is necessary that individuals cooperate with each other to survive the catastrophic failures. Cooperation thus becomes the optimal strategy and absolutely outperforms defection in the game evolution with respect to the "death" mechanism. Our results can be useful for understanding large-scale catastrophe in real-world systems and in particular, they may yield insights into significant social and economical phenomena such as large-scale failures of financial institutions and corporations during an economic recession.

Game changer: the topology of creativity.

PubMed

de Vaan, Mathijs; Stark, David; Vedres, Balazs

2015-01-01

This article examines the sociological factors that explain why some creative teams are able to produce game changers--cultural products that stand out as distinctive while also being critically recognized as outstanding. The authors build on work pointing to structural folding--the network property of a cohesive group whose membership overlaps with that of another cohesive group. They hypothesize that the effects of structural folding on game changing success are especially strong when overlapping groups are cognitively distant. Measuring social distance separately from cognitive distance and distinctiveness independently from critical acclaim, the authors test their hypothesis about structural folding and cognitive diversity by analyzing team reassembly for 12,422 video games and the career histories of 139,727 video game developers. When combined with cognitive distance, structural folding channels and mobilizes a productive tension of rules, roles, and codes that promotes successful innovation. In addition to serving as pipes and prisms, network ties are also the source of tools and tensions.

Online-offline activities and game-playing behaviors of avatars in a massive multiplayer online role-playing game

NASA Astrophysics Data System (ADS)

Jiang, Zhi-Qiang; Zhou, Wei-Xing; Tan, Qun-Zhao

2009-11-01

Massive multiplayer online role-playing games (MMORPGs) are very popular in China, which provides a potential platform for scientific research. We study the online-offline activities of avatars in an MMORPG to understand their game-playing behavior. The statistical analysis unveils that the active avatars can be classified into three types. The avatars of the first type are owned by game cheaters who go online and offline in preset time intervals with the online duration distributions dominated by pulses. The second type of avatars is characterized by a Weibull distribution in the online durations, which is confirmed by statistical tests. The distributions of online durations of the remaining individual avatars differ from the above two types and cannot be described by a simple form. These findings have potential applications in the game industry.

Toward brain correlates of natural behavior: fMRI during violent video games.

PubMed

Mathiak, Klaus; Weber, René

2006-12-01

Modern video games represent highly advanced virtual reality simulations and often contain virtual violence. In a significant amount of young males, playing video games is a quotidian activity, making it an almost natural behavior. Recordings of brain activation with functional magnetic resonance imaging (fMRI) during gameplay may reflect neuronal correlates of real-life behavior. We recorded 13 experienced gamers (18-26 years; average 14 hrs/week playing) while playing a violent first-person shooter game (a violent computer game played in self-perspective) by means of distortion and dephasing reduced fMRI (3 T; single-shot triple-echo echo-planar imaging [EPI]). Content analysis of the video and sound with 100 ms time resolution achieved relevant behavioral variables. These variables explained significant signal variance across large distributed networks. Occurrence of violent scenes revealed significant neuronal correlates in an event-related design. Activation of dorsal and deactivation of rostral anterior cingulate and amygdala characterized the mid-frontal pattern related to virtual violence. Statistics and effect sizes can be considered large at these areas. Optimized imaging strategies allowed for single-subject and for single-trial analysis with good image quality at basal brain structures. We propose that virtual environments can be used to study neuronal processes involved in semi-naturalistic behavior as determined by content analysis. Importantly, the activation pattern reflects brain-environment interactions rather than stimulus responses as observed in classical experimental designs. We relate our findings to the general discussion on social effects of playing first-person shooter games. (c) 2006 Wiley-Liss, Inc.

Gamification of Learning Deactivates the Default Mode Network

PubMed Central

Howard-Jones, Paul A.; Jay, Tim; Mason, Alice; Jones, Harvey

2016-01-01

We hypothesized that embedding educational learning in a game would improve learning outcomes, with increased engagement and recruitment of cognitive resources evidenced by increased activation of working memory network (WMN) and deactivation of default mode network (DMN) regions. In an fMRI study, we compared activity during periods of learning in three conditions that were increasingly game-like: Study-only (when periods of learning were followed by an exemplar question together with its correct answer), Self-quizzing (when periods of learning were followed by a multiple choice question in return for a fixed number of points) and Game-based (when, following each period of learning, participants competed with a peer to answer the question for escalating, uncertain rewards). DMN hubs deactivated as conditions became more game-like, alongside greater self-reported engagement and, in the Game-based condition, higher learning scores. These changes did not occur with any detectable increase in WMN activity. Additionally, ventral striatal activation was associated with responding to questions and receiving positive question feedback. Results support the significance of DMN deactivation for educational learning, and are aligned with recent evidence suggesting DMN and WMN activity may not always be anti-correlated. PMID:26779054

Gamification of Learning Deactivates the Default Mode Network.

PubMed

Howard-Jones, Paul A; Jay, Tim; Mason, Alice; Jones, Harvey

2015-01-01

We hypothesized that embedding educational learning in a game would improve learning outcomes, with increased engagement and recruitment of cognitive resources evidenced by increased activation of working memory network (WMN) and deactivation of default mode network (DMN) regions. In an fMRI study, we compared activity during periods of learning in three conditions that were increasingly game-like: Study-only (when periods of learning were followed by an exemplar question together with its correct answer), Self-quizzing (when periods of learning were followed by a multiple choice question in return for a fixed number of points) and Game-based (when, following each period of learning, participants competed with a peer to answer the question for escalating, uncertain rewards). DMN hubs deactivated as conditions became more game-like, alongside greater self-reported engagement and, in the Game-based condition, higher learning scores. These changes did not occur with any detectable increase in WMN activity. Additionally, ventral striatal activation was associated with responding to questions and receiving positive question feedback. Results support the significance of DMN deactivation for educational learning, and are aligned with recent evidence suggesting DMN and WMN activity may not always be anti-correlated.

[Operation and interaction peculiarities of diagnostic laboratories involved in providing protection from infectious diseases during the XXII Olympic Winter Games and XI Paralympic Winter Games 2014 in Sochi].

PubMed

Onishenko, G G; Popova, A Iu; Bragina, I V; Kuz'kin, B P; Ezhlova, E B; Demina, Iu V; Gus'kov, A S; Ivanov, G E; Chikina, L V; Klindukhova, V P; Grechanaia, T V; Tesheva, S Ch; Kulichenko, A N; Efremenko, D B; Manin, E A; Kuznetsova, I V; Parkhomenko, V V; Kulichenko, O A; Rafeenko, G K; Shcherbina, L I; Zavora, D L; Briukhanov, A F; Eldinova, V E; Iunicheva, Iu V; Derliatko, S K; Komarov, N S

2015-01-01

The experience of the organization and functioning of the laboratory network during the XXII Olympic Winter Games and XI Paralympic Winter Games of 2014 in Sochi is considered. Efforts to establish an effective system of laboratory support, the order of work and interaction of diagnostic laboratories involved in diseases control of population during the Olympic Games are analyzed.

Gaming Sea-based Multinational HA/DR Operations at PACOM Amphibious Leaders Symposium 2016

DTIC Science & Technology

2016-11-01

DISTRIBUTION STATEMENT A. Approved for public release: distribution unlimited. Gaming Sea-based Multinational HA/DR Operations...Marine Corps photo by Cpl. Wesley Timm. Approved by: November 2016 Dr. E.D. McGrady Director, Integration and Gaming Advanced Technology and...TYPE Final2 3. DATES COVERED (From - To) 4. TITLE AND SUBTITLE Gaming Seabased Multinational HA/DR Operations at PACOM 5a. CONTRACT NUMBER N00014-16

Training Social Workers, Clients, and Students in the Use of Rural Natural Helping Networks.

ERIC Educational Resources Information Center

Morris, Judson H.; Hilbert, Judith Cicero

A manual, geared toward training social workers going into rural areas, provides a brief discussion of the natural helping relationships found in rural communities and a simulation game to be used in acquainting social workers, clients, and students with the rural network. Objectives of the simulation game, Nets and Links, are to train people to…

Creating an Online Laboratory

DTIC Science & Technology

2015-03-18

Problem (TSP) to solve, a canonical computer science problem that involves identifying the shortest itinerary for a hypothetical salesman traveling among a...also created working versions of the travelling salesperson problem , prisoners’ dilemma, public goods game, ultimatum game, word ladders, and...the task within networks of others performing the task. Thus, we built five problems which could be embedded in networks: the traveling salesperson

Emergent Complexity in Conway's Game of Life

NASA Astrophysics Data System (ADS)

Gotts, Nick

It is shown that both small, finite patterns and random infinite very low density ("sparse") arrays of the Game of Life can produce emergent structures and processes of great complexity, through ramifying feedback networks and cross-scale interactions. The implications are discussed: it is proposed that analogous networks and interactions may have been precursors to natural selection in the real world.

Local communities obstruct global consensus: Naming game on multi-local-world networks

NASA Astrophysics Data System (ADS)

Lou, Yang; Chen, Guanrong; Fan, Zhengping; Xiang, Luna

2018-02-01

Community structure is essential for social communications, where individuals belonging to the same community are much more actively interacting and communicating with each other than those in different communities within the human society. Naming game, on the other hand, is a social communication model that simulates the process of learning a name of an object within a community of humans, where the individuals can generally reach global consensus asymptotically through iterative pair-wise conversations. The underlying network indicates the relationships among the individuals. In this paper, three typical topologies, namely random-graph, small-world and scale-free networks, are employed, which are embedded with the multi-local-world community structure, to study the naming game. Simulations show that (1) the convergence process to global consensus is getting slower as the community structure becomes more prominent, and eventually might fail; (2) if the inter-community connections are sufficiently dense, neither the number nor the size of the communities affects the convergence process; and (3) for different topologies with the same (or similar) average node-degree, local clustering of individuals obstruct or prohibit global consensus to take place. The results reveal the role of local communities in a global naming game in social network studies.

Game Theory-Based Cooperation for Underwater Acoustic Sensor Networks: Taxonomy, Review, Research Challenges and Directions

PubMed Central

Muhammed, Dalhatu; Anisi, Mohammad Hossein; Vargas-Rosales, Cesar; Khan, Anwar

2018-01-01

Exploring and monitoring the underwater world using underwater sensors is drawing a lot of attention these days. In this field cooperation between acoustic sensor nodes has been a critical problem due to the challenging features such as acoustic channel failure (sound signal), long propagation delay of acoustic signal, limited bandwidth and loss of connectivity. There are several proposed methods to improve cooperation between the nodes by incorporating information/game theory in the node’s cooperation. However, there is a need to classify the existing works and demonstrate their performance in addressing the cooperation issue. In this paper, we have conducted a review to investigate various factors affecting cooperation in underwater acoustic sensor networks. We study various cooperation techniques used for underwater acoustic sensor networks from different perspectives, with a concentration on communication reliability, energy consumption, and security and present a taxonomy for underwater cooperation. Moreover, we further review how the game theory can be applied to make the nodes cooperate with each other. We further analyze different cooperative game methods, where their performance on different metrics is compared. Finally, open issues and future research direction in underwater acoustic sensor networks are highlighted. PMID:29389874

Effects of training strategies implemented in a complex videogame on functional connectivity of attentional networks.

PubMed

Voss, Michelle W; Prakash, Ruchika Shaurya; Erickson, Kirk I; Boot, Walter R; Basak, Chandramallika; Neider, Mark B; Simons, Daniel J; Fabiani, Monica; Gratton, Gabriele; Kramer, Arthur F

2012-01-02

We used the Space Fortress videogame, originally developed by cognitive psychologists to study skill acquisition, as a platform to examine learning-induced plasticity of interacting brain networks. Novice videogame players learned Space Fortress using one of two training strategies: (a) focus on all aspects of the game during learning (fixed priority), or (b) focus on improving separate game components in the context of the whole game (variable priority). Participants were scanned during game play using functional magnetic resonance imaging (fMRI), both before and after 20 h of training. As expected, variable priority training enhanced learning, particularly for individuals who initially performed poorly. Functional connectivity analysis revealed changes in brain network interaction reflective of more flexible skill learning and retrieval with variable priority training, compared to procedural learning and skill implementation with fixed priority training. These results provide the first evidence for differences in the interaction of large-scale brain networks when learning with different training strategies. Our approach and findings also provide a foundation for exploring the brain plasticity involved in transfer of trained abilities to novel real-world tasks such as driving, sport, or neurorehabilitation. Copyright © 2011 Elsevier Inc. All rights reserved.

Game Theory-Based Cooperation for Underwater Acoustic Sensor Networks: Taxonomy, Review, Research Challenges and Directions.

PubMed

Muhammed, Dalhatu; Anisi, Mohammad Hossein; Zareei, Mahdi; Vargas-Rosales, Cesar; Khan, Anwar

2018-02-01

Exploring and monitoring the underwater world using underwater sensors is drawing a lot of attention these days. In this field cooperation between acoustic sensor nodes has been a critical problem due to the challenging features such as acoustic channel failure (sound signal), long propagation delay of acoustic signal, limited bandwidth and loss of connectivity. There are several proposed methods to improve cooperation between the nodes by incorporating information/game theory in the node's cooperation. However, there is a need to classify the existing works and demonstrate their performance in addressing the cooperation issue. In this paper, we have conducted a review to investigate various factors affecting cooperation in underwater acoustic sensor networks. We study various cooperation techniques used for underwater acoustic sensor networks from different perspectives, with a concentration on communication reliability, energy consumption, and security and present a taxonomy for underwater cooperation. Moreover, we further review how the game theory can be applied to make the nodes cooperate with each other. We further analyze different cooperative game methods, where their performance on different metrics is compared. Finally, open issues and future research direction in underwater acoustic sensor networks are highlighted.

Mixed strategy and coevolution dynamics in social networks

NASA Astrophysics Data System (ADS)

Zhong, Weicai; Abbass, Hussein A.; Bender, Axel; Liu, Jing

2011-01-01

We investigate coevolution dynamics of both individual strategies and social ties as they adapt within the snowdrift game with mixed strategies. We propose a partner selection mechanism based on the concept of trust. Here trust is considered an instrument for an individual both selecting the right partners and being selected amongst other potential partners. Based on her local views of the system, the focal individual dismisses the link from the partner with the lowest trust and rewires to the partner’s partner with the highest trust. It is shown that such a trust-based partner switching mechanism favors the emergence of cooperators. Furthermore, when the number of an individual’s partners is restricted (which is a metaphor of limited capacities and capabilities of an individual in real environments), surprising assortative mixing patterns are formed in the emerging network and change the network’s degree distribution from a power-law distribution to an asymmetrically U-shaped distribution. This plays a leading role in preventing global avalanches triggered by perturbations acting on the state of the highly connected individuals.

LLCySA: Making Sense of Cyberspace

DTIC Science & Technology

2014-01-01

data center. His other activities include the development of immersive 3D environments leveraging video- game technology to provide a multiplayer ...exploring data-driven approaches to network protection. Imagine a cyber analyst navigating a three-dimen- sional (3D) game , walking down virtual office...because of information overload. One approach to this challenge leverages technol- ogy utilized in the 3D gaming industry. The video- game medium

Prisoner's Dilemma Applied and in the Classroom: The TV Game Show "Friend or Foe"

ERIC Educational Resources Information Center

Coe, Paul R.; Alonzi, Loreto Peter; Condon, Daniel; Butterworth, William T.

2007-01-01

Prisoner's Dilemma is a common game theory scenario in which two players must choose between acting cooperatively or out of pure self-interest. What a player decides affects not only his own outcome but also that of the other player. "Friend or Foe," a TV game show that has appeared on the cable Game Show Network (GSN), places pairs of contestants…

Impulsive Internet Game Play Is Associated With Increased Functional Connectivity Between the Default Mode and Salience Networks in Depressed Patients With Short Allele of Serotonin Transporter Gene.

PubMed

Hong, Ji Sun; Kim, Sun Mi; Bae, Sujin; Han, Doug Hyun

2018-01-01

Problematic Internet game play is often accompanied by major depressive disorder (MDD). Depression seems to be closely related to altered functional connectivity (FC) within (and between) the default mode network (DMN) and salience network. In addition, serotonergic neurotransmission may regulate the symptoms of depression, including impulsivity, potentially by modulating the DMN. We hypothesized that altered connectivity between the DMN and salience network could mediate an association between the 5HTTLPR genotype and impulsivity in patients with depression. A total of 54 participants with problematic Internet game play and MDD completed the research protocol. We genotyped for 5HTTLPR and assessed the DMN FC using resting-state functional magnetic resonance imaging. The severity of Internet game play, depressive symptoms, anxiety, attention and impulsivity, and behavioral inhibition and activation were assessed using the Young Internet Addiction Scale (YIAS), Beck Depressive Inventory, Beck Anxiety Inventory (BAI), Korean Attention Deficit Hyperactivity Disorder scale, and the Behavioral Inhibition and Activation Scales (BIS-BAS), respectively. The SS allele was associated with increased FC within the DMN, including the middle prefrontal cortex (MPFC) to the posterior cingulate cortex, and within the salience network, including the right supramarginal gyrus (SMG) to the right rostral prefrontal cortex (RPFC), right anterior insular (AInsular) to right SMG, anterior cingulate cortex (ACC) to left RPFC, and left AInsular to right RPFC, and between the DMN and salience network, including the MPFC to the ACC. In addition, the FC from the MPFC to ACC positively correlated with the BIS and YIAS scores in the SS allele group. The SS allele of 5HTTLPR might modulate the FC within and between the DMN and salience network, which may ultimately be a risk factor for impulsive Internet game play in patients with MDD.

Effect of direct reciprocity and network structure on continuing prosperity of social networking services.

PubMed

Osaka, Kengo; Toriumi, Fujio; Sugawara, Toshihauru

2017-01-01

Social networking services (SNSs) are widely used as communicative tools for a variety of purposes. SNSs rely on the users' individual activities associated with some cost and effort, and thus it is not known why users voluntarily continue to participate in SNSs. Because the structures of SNSs are similar to that of the public goods (PG) game, some studies have focused on why voluntary activities emerge as an optimal strategy by modifying the PG game. However, their models do not include direct reciprocity between users, even though reciprocity is a key mechanism that evolves and sustains cooperation in human society. We developed an abstract SNS model called the reciprocity rewards and meta-rewards games that include direct reciprocity by extending the existing models. Then, we investigated how direct reciprocity in an SNS facilitates cooperation that corresponds to participation in SNS by posting articles and comments and how the structure of the networks of users exerts an influence on the strategies of users using the reciprocity rewards game. We run reciprocity rewards games on various complex networks and an instance network of Facebook and found that two types of stable cooperation emerged. First, reciprocity slightly improves the rate of cooperation in complete graphs but the improvement is insignificant because of the instability of cooperation. However, this instability can be avoided by making two assumptions: high degree of fun, i.e. articles are read with high probability, and different attitudes to reciprocal and non-reciprocal agents. We then propose the concept of half free riders to explain what strategy sustains cooperation-dominant situations. Second, we indicate that a certain WS network structure affects users' optimal strategy and facilitates stable cooperation without any extra assumptions. We give a detailed analysis of the different characteristics of the two types of cooperation-dominant situations and the effect of the memory of reciprocal agents on cooperation.

Mesoscopic Effects in an Agent-Based Bargaining Model in Regular Lattices

PubMed Central

Poza, David J.; Santos, José I.; Galán, José M.; López-Paredes, Adolfo

2011-01-01

The effect of spatial structure has been proved very relevant in repeated games. In this work we propose an agent based model where a fixed finite population of tagged agents play iteratively the Nash demand game in a regular lattice. The model extends the multiagent bargaining model by Axtell, Epstein and Young [1] modifying the assumption of global interaction. Each agent is endowed with a memory and plays the best reply against the opponent's most frequent demand. We focus our analysis on the transient dynamics of the system, studying by computer simulation the set of states in which the system spends a considerable fraction of the time. The results show that all the possible persistent regimes in the global interaction model can also be observed in this spatial version. We also find that the mesoscopic properties of the interaction networks that the spatial distribution induces in the model have a significant impact on the diffusion of strategies, and can lead to new persistent regimes different from those found in previous research. In particular, community structure in the intratype interaction networks may cause that communities reach different persistent regimes as a consequence of the hindering diffusion effect of fluctuating agents at their borders. PMID:21408019

Mesoscopic effects in an agent-based bargaining model in regular lattices.

PubMed

Poza, David J; Santos, José I; Galán, José M; López-Paredes, Adolfo

2011-03-09

The effect of spatial structure has been proved very relevant in repeated games. In this work we propose an agent based model where a fixed finite population of tagged agents play iteratively the Nash demand game in a regular lattice. The model extends the multiagent bargaining model by Axtell, Epstein and Young modifying the assumption of global interaction. Each agent is endowed with a memory and plays the best reply against the opponent's most frequent demand. We focus our analysis on the transient dynamics of the system, studying by computer simulation the set of states in which the system spends a considerable fraction of the time. The results show that all the possible persistent regimes in the global interaction model can also be observed in this spatial version. We also find that the mesoscopic properties of the interaction networks that the spatial distribution induces in the model have a significant impact on the diffusion of strategies, and can lead to new persistent regimes different from those found in previous research. In particular, community structure in the intratype interaction networks may cause that communities reach different persistent regimes as a consequence of the hindering diffusion effect of fluctuating agents at their borders.

The effect of the topology on the spatial ultimatum game

NASA Astrophysics Data System (ADS)

Kuperman, M. N.; Risau-Gusman, S.

2008-03-01

In this work we present an analysis of a spatially non homogeneous ultimatum game. By considering different underlying topologies as substrates on top of which the game takes place we obtain nontrivial behaviors for the evolution of the strategies of the players. We analyze separately the effect of the size of the neighborhood and the spatial structure. Whereas this last effect is the most significant one, we show that even for disordered networks and provided the neighborhood of each site is small, the results can be significantly different from those obtained in the case of fully connected networks.

RICH Economic Games for Networked Relationships and Communities: Development and Preliminary Validation in Yasawa, Fiji

ERIC Educational Resources Information Center

Gervais, Matthew M.

2017-01-01

Experimental economic games reveal significant population variation in human social behavior. However, most protocols involve anonymous recipients, limiting their validity to fleeting interactions. Understanding human relationship dynamics will require methods with the virtues of economic games that also tap recipient identity-conditioned…

Remote Labs and Game-Based Learning for Process Control

ERIC Educational Resources Information Center

Zualkernan, Imran A.; Husseini, Ghaleb A.; Loughlin, Kevin F.; Mohebzada, Jamshaid G.; El Gaml, Moataz

2013-01-01

Social networking platforms and computer games represent a natural informal learning environment for the current generation of learners in higher education. This paper explores the use of game-based learning in the context of an undergraduate chemical engineering remote laboratory. Specifically, students are allowed to manipulate chemical…

Constructing Game Agents from Video of Human Behavior

DTIC Science & Technology

2009-01-01

Future Work Constructing autonomous agents is an important task in video game development. Games such as Quake, Warcraft III, and Halo 2 (Damian 2005...Vision. Rio de Janeiro, Brazil: IEEE Press. Kelley, J. P.; Botea, A.; and Koenig, S. 2008. Offline planning with hierarchical task networks in video ...

Tactical Behavior Mining of a Soldier-Based Gaming Environment (Briefing Charts)

DTIC Science & Technology

2016-05-23

U.S. ARMY TANK AUTOMOTIVE RESEARCH, DEVELOPMENT AND ENGINEERING CENTER Tactical Behavior Mining of a Soldier-Based Gaming Environment 5/23/2016 …Plus...Distribution Statement A. Approved for public release; distribution is unlimited. 4 One Solution: Use a Physics-Based Game Environment TARDEC VIRTUAL...EXPERIMENTS CAPABILITY  VBS3 Training Game  ុ Soldier Experiments  2-3 Days = Several Refights  Lickert Subjective Questionaires  ESP Engine

Dynamic social networks facilitate cooperation in the N-player Prisoner’s Dilemma

NASA Astrophysics Data System (ADS)

Rezaei, Golriz; Kirley, Michael

2012-12-01

Understanding how cooperative behaviour evolves in network communities, where the individual members interact via social dilemma games, is an on-going challenge. In this paper, we introduce a social network based model to investigate the evolution of cooperation in the N-player Prisoner’s Dilemma game. As such, this work complements previous studies focused on multi-player social dilemma games and endogenous networks. Agents in our model, employ different game-playing strategies reflecting varying cognitive capacities. When an agent plays cooperatively, a social link is formed with each of the other N-1 group members. Subsequent cooperative actions reinforce this link. However, when an agent defects, the links in the social network are broken. Computational simulations across a range of parameter settings are used to examine different scenarios: varying population and group sizes; the group formation process (or partner selection); and agent decision-making strategies under varying dilemma constraints (cost-to-benefit ratios), including a “discriminator” strategy where the action is based on a function of the weighted links within an agent’s social network. The simulation results show that the proposed social network model is able to evolve and maintain cooperation. As expected, as the value of N increases the equilibrium proportion of cooperators in the population decreases. In addition, this outcome is dependent on the dilemma constraint (cost-to-benefit ratio). However, in some circumstances the dynamic social network plays an increasingly important role in promoting and sustaining cooperation, especially when the agents adopt the discriminator strategy. The adjustment of social links results in the formation of communities of “like-minded” agents. Subsequently, this local optimal behaviour promotes the evolution of cooperative behaviour at the system level.

Interactive learning in 2×2 normal form games by neural network agents

NASA Astrophysics Data System (ADS)

Spiliopoulos, Leonidas

2012-11-01

This paper models the learning process of populations of randomly rematched tabula rasa neural network (NN) agents playing randomly generated 2×2 normal form games of all strategic classes. This approach has greater external validity than the existing models in the literature, each of which is usually applicable to narrow subsets of classes of games (often a single game) and/or to fixed matching protocols. The learning prowess of NNs with hidden layers was impressive as they learned to play unique pure strategy equilibria with near certainty, adhered to principles of dominance and iterated dominance, and exhibited a preference for risk-dominant equilibria. In contrast, perceptron NNs were found to perform significantly worse than hidden layer NN agents and human subjects in experimental studies.

Authoring Effective Demonstrations

DTIC Science & Technology

2007-06-22

Battle Focused Training. Washington, DC: Department of the Army. Fu, D., Jensen, R., & Hinkelman, E . (2007). “Evaluating Game Technologies for...Stottler Henke Associates, Inc. Univ. of Central Florida Elizabeth Hinkelman Don Lampton Galactic Village Games , LLC. Army Research Institute...training, and distributed game -based architectures contribute an added benefit of wide accessibility. Reusable and distributable virtual training

Double-dealing behavior potentially promotes cooperation in evolutionary prisoner's dilemma games

NASA Astrophysics Data System (ADS)

Dai, Qionglin; Li, Haihong; Cheng, Hongyan; Li, Yuting; Yang, Junzhong

2010-11-01

We investigate the effects of double-dealing behavior on cooperation in evolutionary games. Each individual in a population has two attributes: character and action. One's action may be consistent with one's character or not. We provide analytical results by a mean-field description of evolutionary prisoner's dilemma games (PDGs). Moreover, we give numerical results on different networks, ranging from square lattices to scale-free networks (SFNs). Two important conclusions have been drawn from the results on SFNs. Firstly, if only non-influential individuals (those with low degrees) have chances of becoming double-dealers, cooperation is certain to deteriorate. Secondly, when influential individuals (those with high degrees) adopt double-dealing behavior moderately, cooperation would be enhanced, which is in opposition to the traditional belief. These results help us to understand better the social phenomenon of the existence of double-dealers. In addition to the PDG, other types of games including the snowdrift game, the stag-hunt game and the harmony game have also been studied on our model. The results for these three games are also presented, which are consistent with the results for the PDG qualitatively. Furthermore, we consider our model under the co-evolution framework, in which the probability of an individual changing into a double-dealer and the individual strategy both could evolve during the evolutionary process.

Spatio-temporal dynamics of security investments in an interdependent risk environment

NASA Astrophysics Data System (ADS)

Shafi, Kamran; Bender, Axel; Zhong, Weicai; Abbass, Hussein A.

2012-10-01

In a globalised world where risks spread through contagion, the decision of an entity to invest in securing its premises from stochastic risks no longer depends solely on its own actions but also on the actions of other interacting entities in the system. This phenomenon is commonly seen in many domains including airline, logistics and computer security and is referred to as Interdependent Security (IDS). An IDS game models this decision problem from a game-theoretic perspective and deals with the behavioural dynamics of risk-reduction investments in such settings. This paper enhances this model and investigates the spatio-temporal aspects of the IDS games. The spatio-temporal dynamics are studied using simple replicator dynamics on a variety of network structures and for various security cost tradeoffs that lead to different Nash equilibria in an IDS game. The simulation results show that the neighbourhood configuration has a greater effect on the IDS game dynamics than network structure. An in-depth empirical analysis of game dynamics is carried out on regular graphs, which leads to the articulation of necessary and sufficient conditions for dominance in IDS games under spatial constraints.

Neural contributions to flow experience during video game playing.

PubMed

Klasen, Martin; Weber, René; Kircher, Tilo T J; Mathiak, Krystyna A; Mathiak, Klaus

2012-04-01

Video games are an exciting part of new media. Although game play has been intensively studied, the underlying neurobiology is still poorly understood. Flow theory is a well-established model developed to describe subjective game experience. In 13 healthy male subjects, we acquired fMRI data during free play of a video game and analyzed brain activity based on the game content. In accordance with flow theory, we extracted the following factors from the game content: (i) balance between ability and challenge; (ii) concentration and focus; (iii) direct feedback of action results; (iv) clear goals; and (v) control over the situation/activity. We suggest that flow is characterized by specific neural activation patterns and that the latter can be assessed-at least partially-by content factors contributing to the emergence of flow. Each of the content factors was characterized by specific and distinguishable brain activation patterns, encompassing reward-related midbrain structures, as well as cognitive and sensorimotor networks. The activation of sensory and motor networks in the conjunction analyses underpinned the central role of simulation for flow experience. Flow factors can be validated with functional brain imaging which can improve the understanding of human emotions and motivational processes during media entertainment.

Neural contributions to flow experience during video game playing

PubMed Central

Weber, René; Kircher, Tilo T. J.; Mathiak, Krystyna A.; Mathiak, Klaus

2012-01-01

Video games are an exciting part of new media. Although game play has been intensively studied, the underlying neurobiology is still poorly understood. Flow theory is a well-established model developed to describe subjective game experience. In 13 healthy male subjects, we acquired fMRI data during free play of a video game and analyzed brain activity based on the game content. In accordance with flow theory, we extracted the following factors from the game content: (i) balance between ability and challenge; (ii) concentration and focus; (iii) direct feedback of action results; (iv) clear goals; and (v) control over the situation/activity. We suggest that flow is characterized by specific neural activation patterns and that the latter can be assessed—at least partially—by content factors contributing to the emergence of flow. Each of the content factors was characterized by specific and distinguishable brain activation patterns, encompassing reward-related midbrain structures, as well as cognitive and sensorimotor networks. The activation of sensory and motor networks in the conjunction analyses underpinned the central role of simulation for flow experience. Flow factors can be validated with functional brain imaging which can improve the understanding of human emotions and motivational processes during media entertainment. PMID:21596764

Social Networks and Cooperation in Hunter-Gatherers

PubMed Central

Apicella, Coren L.; Marlowe, Frank W.; Fowler, James H.; Christakis, Nicholas A.

2011-01-01

Social networks exhibit striking structural regularities1,2, and theory and evidence suggest that they may have played a role in the development of large-scale cooperation in humans3–7. Here, we characterize the social networks of the Hadza, an evolutionarily relevant population of hunter-gatherers8. We show that Hadza networks exhibit important properties also seen in modernized networks, including a skewed degree distribution, degree assortativity, transitivity, reciprocity, geographic decay, and homophily. Moreover, we demonstrate that Hadza camps exhibit high between-group and low within-group variation in public goods game donations. Network ties are also more likely between people who give the same amount, and the similarity in cooperative behaviour extends up to two degrees of separation. Finally, social distance appears to be as important as genetic relatedness and physical proximity in explaining assortativity in cooperation. Our results suggest that certain elements of social network structure may have been present at an early point in human history; that early humans may have formed ties with both kin and non-kin based, in part, on their tendency to cooperate; and that social networks may have contributed to the emergence of cooperation. PMID:22281599

Strategic tradeoffs in competitor dynamics on adaptive networks.

PubMed

Hébert-Dufresne, Laurent; Allard, Antoine; Noël, Pierre-André; Young, Jean-Gabriel; Libby, Eric

2017-08-08

Recent empirical work highlights the heterogeneity of social competitions such as political campaigns: proponents of some ideologies seek debate and conversation, others create echo chambers. While symmetric and static network structure is typically used as a substrate to study such competitor dynamics, network structure can instead be interpreted as a signature of the competitor strategies, yielding competition dynamics on adaptive networks. Here we demonstrate that tradeoffs between aggressiveness and defensiveness (i.e., targeting adversaries vs. targeting like-minded individuals) creates paradoxical behaviour such as non-transitive dynamics. And while there is an optimal strategy in a two competitor system, three competitor systems have no such solution; the introduction of extreme strategies can easily affect the outcome of a competition, even if the extreme strategies have no chance of winning. Not only are these results reminiscent of classic paradoxical results from evolutionary game theory, but the structure of social networks created by our model can be mapped to particular forms of payoff matrices. Consequently, social structure can act as a measurable metric for social games which in turn allows us to provide a game theoretical perspective on online political debates.

Crucial role of strategy updating for coexistence of strategies in interaction networks.

PubMed

Zhang, Jianlei; Zhang, Chunyan; Cao, Ming; Weissing, Franz J

2015-04-01

Network models are useful tools for studying the dynamics of social interactions in a structured population. After a round of interactions with the players in their local neighborhood, players update their strategy based on the comparison of their own payoff with the payoff of one of their neighbors. Here we show that the assumptions made on strategy updating are of crucial importance for the strategy dynamics. In the first step, we demonstrate that seemingly small deviations from the standard assumptions on updating have major implications for the evolutionary outcome of two cooperation games: cooperation can more easily persist in a Prisoner's Dilemma game, while it can go more easily extinct in a Snowdrift game. To explain these outcomes, we develop a general model for the updating of states in a network that allows us to derive conditions for the steady-state coexistence of states (or strategies). The analysis reveals that coexistence crucially depends on the number of agents consulted for updating. We conclude that updating rules are as important for evolution on a network as network structure and the nature of the interaction.

Crucial role of strategy updating for coexistence of strategies in interaction networks

NASA Astrophysics Data System (ADS)

Zhang, Jianlei; Zhang, Chunyan; Cao, Ming; Weissing, Franz J.

2015-04-01

Network models are useful tools for studying the dynamics of social interactions in a structured population. After a round of interactions with the players in their local neighborhood, players update their strategy based on the comparison of their own payoff with the payoff of one of their neighbors. Here we show that the assumptions made on strategy updating are of crucial importance for the strategy dynamics. In the first step, we demonstrate that seemingly small deviations from the standard assumptions on updating have major implications for the evolutionary outcome of two cooperation games: cooperation can more easily persist in a Prisoner's Dilemma game, while it can go more easily extinct in a Snowdrift game. To explain these outcomes, we develop a general model for the updating of states in a network that allows us to derive conditions for the steady-state coexistence of states (or strategies). The analysis reveals that coexistence crucially depends on the number of agents consulted for updating. We conclude that updating rules are as important for evolution on a network as network structure and the nature of the interaction.

Bridging Social Capital in Online Communities: Heterogeneity and Social Tolerance of Online Game Players in Japan

ERIC Educational Resources Information Center

Kobayashi, Tetsuro

2010-01-01

This article examines the democratic potential of online communities by investigating the influence of network heterogeneity on social tolerance in an online gaming environment. Online game communities are potential sources of bridging social capital because they tend to be relatively heterogeneous. Causal analyses are conducted using structural…

"The Source": An Alternate Reality Game to Spark STEM Interest and Learning among Underrepresented Youth

ERIC Educational Resources Information Center

Gilliam, Melissa; Bouris, Alida; Hill, Brandon; Jagoda, Patrick

2016-01-01

Alternate Reality Games (ARGs) are multiplayer role-playing games that use the real world as their primary platform and incorporate a range of media, including video, audio, email, mobile technologies, websites, live performance, and social networks. This paper describes the development, implementation, and player reception of "The…

Leadership in MMOGs: A Field of Research on Virtual Teams

ERIC Educational Resources Information Center

Mysirlaki, Sofia; Paraskeva, Fotini

2012-01-01

As our need for collaboration constantly grows, new tools have emerged to connect us in social networks, supporting the development of online communities, such as online games and virtual worlds. MMOGs (Massively Multiplayer Online Games) and MMORPGs (Massively Multiplayer Online Role-Playing Games) are complex systems, in which players are…

The WoW Factor

ERIC Educational Resources Information Center

Demski, Jennifer

2009-01-01

For a growing group of educators, the online role-playing game World of Warcraft, Blizzard Entertainment's massively popular massively multiplayer online role-playing game (MMORPG), is a place to go to relax, network, and discover potential learning strategies-- and slay a few monsters if they get in the way. The online role-playing game World of…

Games and Web 2.0: A Winning Combination for Millennials

ERIC Educational Resources Information Center

Spiegelman, Marsha; Glass, Richard

2009-01-01

Gaming and social networking define the millennial student. This research focuses on an evolving collaboration between 2 faculty members of different disciplines who merged Web 2.0 and game scenarios to infuse research techniques as integral components of math/computer science courses. Blogs and wikis facilitated student-faculty interaction beyond…

Tactical AI in Real Time Strategy Games

DTIC Science & Technology

2015-03-26

TACTICAL AI IN REAL TIME STRATEGY GAMES THESIS Donald A. Gruber, Capt, USAF AFIT-ENG-MS-15-M-021 DEPARTMENT OF THE AIR FORCE AIR UNIVERSITY AIR FORCE...protection in the United States. AFIT-ENG-MS-15-M-021 TACTICAL AI IN REAL TIME STRATEGY GAMES THESIS Presented to the Faculty Department of Electrical...DISTRIBUTION STATEMENT A APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED. AFIT-ENG-MS-15-M-021 TACTICAL AI IN REAL TIME STRATEGY GAMES THESIS Donald A

Network structures between strategies in iterated prisoners' dilemma games

NASA Astrophysics Data System (ADS)

Kim, Young Jin; Roh, Myungkyoon; Son, Seung-Woo

2014-02-01

We use replicator dynamics to study an iterated prisoners' dilemma game with memory. In this study, we investigate the characteristics of all 32 possible strategies with a single-step memory by observing the results when each strategy encounters another one. Based on these results, we define similarity measures between the 32 strategies and perform a network analysis of the relationship between the strategies by constructing a strategies network. Interestingly, we find that a win-lose circulation, like rock-paper-scissors, exists between strategies and that the circulation results from one unusual strategy.

Ramifying feedback networks, cross-scale interactions, and emergent quasi individuals in Conway's game of Life.

PubMed

Gotts, Nicholas M

2009-01-01

Small patterns of state 1 cells on an infinite, otherwise empty array of Conway's game of Life can produce sets of growing structures resembling in significant ways a population of spatially situated individuals in a nonuniform, highly structured environment. Ramifying feedback networks and cross-scale interactions play a central role in the emergence and subsequent dynamics of the quasi population. The implications are discussed: It is proposed that analogous networks and interactions may have been precursors to natural selection in the real world.

Inequality and visibility of wealth in experimental social networks.

PubMed

Nishi, Akihiro; Shirado, Hirokazu; Rand, David G; Christakis, Nicholas A

2015-10-15

Humans prefer relatively equal distributions of resources, yet societies have varying degrees of economic inequality. To investigate some of the possible determinants and consequences of inequality, here we perform experiments involving a networked public goods game in which subjects interact and gain or lose wealth. Subjects (n = 1,462) were randomly assigned to have higher or lower initial endowments, and were embedded within social networks with three levels of economic inequality (Gini coefficient = 0.0, 0.2, and 0.4). In addition, we manipulated the visibility of the wealth of network neighbours. We show that wealth visibility facilitates the downstream consequences of initial inequality-in initially more unequal situations, wealth visibility leads to greater inequality than when wealth is invisible. This result reflects a heterogeneous response to visibility in richer versus poorer subjects. We also find that making wealth visible has adverse welfare consequences, yielding lower levels of overall cooperation, inter-connectedness, and wealth. High initial levels of economic inequality alone, however, have relatively few deleterious welfare effects.

Defense strategies for asymmetric networked systems under composite utilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rao, Nageswara S.; Ma, Chris Y. T.; Hausken, Kjell

We consider an infrastructure of networked systems with discrete components that can be reinforced at certain costs to guard against attacks. The communications network plays a critical, asymmetric role of providing the vital connectivity between the systems. We characterize the correlations within this infrastructure at two levels using (a) aggregate failure correlation function that specifies the infrastructure failure probability giventhe failure of an individual system or network, and (b) first order differential conditions on system survival probabilities that characterize component-level correlations. We formulate an infrastructure survival game between an attacker and a provider, who attacks and reinforces individual components, respectively.more » They use the composite utility functions composed of a survival probability term and a cost term, and the previously studiedsum-form and product-form utility functions are their special cases. At Nash Equilibrium, we derive expressions for individual system survival probabilities and the expected total number of operational components. We apply and discuss these estimates for a simplified model of distributed cloud computing infrastructure« less

Bribery games on interdependent complex networks.

PubMed

Verma, Prateek; Nandi, Anjan K; Sengupta, Supratim

2018-08-07

Bribe demands present a social conflict scenario where decisions have wide-ranging economic and ethical consequences. Nevertheless, such incidents occur daily in many countries across the globe. Harassment bribery constitute a significant sub-set of such bribery incidents where a government official demands a bribe for providing a service to a citizen legally entitled to it. We employ an evolutionary game-theoretic framework to analyse the evolution of corrupt and honest strategies in structured populations characterized by an interdependent complex network. The effects of changing network topology, average number of links and asymmetry in size of the citizen and officer population on the proliferation of incidents of bribery are explored. A complex network topology is found to be beneficial for the dominance of corrupt strategies over a larger region of phase space when compared with the outcome for a regular network, for equal citizen and officer population sizes. However, the extent of the advantage depends critically on the network degree and topology. A different trend is observed when there is a difference between the citizen and officer population sizes. Under those circumstances, increasing randomness of the underlying citizen network can be beneficial to the fixation of honest officers up to a certain value of the network degree. Our analysis reveals how the interplay between network topology, connectivity and strategy update rules can affect population level outcomes in such asymmetric games. Copyright © 2018 Elsevier Ltd. All rights reserved.

Network marketing with bounded rationality and partial information

NASA Astrophysics Data System (ADS)

Kiet, Hoang Anh Tuan; Kim, Beom Jun

2008-08-01

Network marketing has been proposed and used as a way to spread the product information to consumers through social connections. We extend the previous game model of the network marketing on a small-world tree network and propose two games: In the first model with the bounded rationality, each consumer makes purchase decision stochastically, while in the second model, consumers get only partial information due to the finite length of social connections. Via extensive numerical simulations, we find that as the rationality is enhanced not only the consumer surplus but also the firm’s profit is increased. The implication of our results is also discussed.

A Study on Standard Competition with Network Effect Based on Evolutionary Game Model

NASA Astrophysics Data System (ADS)

Wang, Ye; Wang, Bingdong; Li, Kangning

Owing to networks widespread in modern society, standard competition with network effect is now endowed with new connotation. This paper aims to study the impact of network effect on standard competition; it is organized in the mode of "introduction-model setup-equilibrium analysis-conclusion". Starting from a well-structured model of evolutionary game, it is then extended to a dynamic analysis. This article proves both theoretically and empirically that whether or not a standard can lead the market trends depends on the utility it would bring, and the author also discusses some advisable strategies revolving around the two factors of initial position and border break.

Cyber-Ed.

ERIC Educational Resources Information Center

Ruben, Barbara

1994-01-01

Reviews a number of interactive environmental computer education networks and software packages. Computer networks include National Geographic Kids Network, Global Lab, and Global Rivers Environmental Education Network. Computer software involve environmental decision making, simulation games, tropical rainforests, the ocean, the greenhouse…

A General Bayesian Network Approach to Analyzing Online Game Item Values and Its Influence on Consumer Satisfaction and Purchase Intention

NASA Astrophysics Data System (ADS)

Lee, Kun Chang; Park, Bong-Won

Many online game users purchase game items with which to play free-to-play games. Because of a lack of research into which there is no specified framework for categorizing the values of game items, this study proposes four types of online game item values based on an analysis of literature regarding online game characteristics. It then proposes to investigate how online game users perceive satisfaction and purchase intention from the proposed four types of online game item values. Though regression analysis has been used frequently to answer this kind of research question, we propose a new approach, a General Bayesian Network (GBN), which can be performed in an understandable way without sacrificing predictive accuracy. Conventional techniques, such as regression analysis, do not provide significant explanation for this kind of problem because they are fixed to a linear structure and are limited in explaining why customers are likely to purchase game items and if they are satisfied with their purchases. In contrast, the proposed GBN provides a flexible underlying structure based on questionnaire survey data and offers robust decision support on this kind of research question by identifying its causal relationships. To illustrate the validity of GBN in solving the research question in this study, 327 valid questionnaires were analyzed using GBN with what-if and goal-seeking approaches. The experimental results were promising and meaningful in comparison with regression analysis results.

Ensemble method: Community detection based on game theory

NASA Astrophysics Data System (ADS)

Zhang, Xia; Xia, Zhengyou; Xu, Shengwu; Wang, J. D.

2014-08-01

Timely and cost-effective analytics over social network has emerged as a key ingredient for success in many businesses and government endeavors. Community detection is an active research area of relevance to analyze online social network. The problem of selecting a particular community detection algorithm is crucial if the aim is to unveil the community structure of a network. The choice of a given methodology could affect the outcome of the experiments because different algorithms have different advantages and depend on tuning specific parameters. In this paper, we propose a community division model based on the notion of game theory, which can combine advantages of previous algorithms effectively to get a better community classification result. By making experiments on some standard dataset, it verifies that our community detection model based on game theory is valid and better.

A Game Theoretic Optimization Method for Energy Efficient Global Connectivity in Hybrid Wireless Sensor Networks

PubMed Central

Lee, JongHyup; Pak, Dohyun

2016-01-01

For practical deployment of wireless sensor networks (WSN), WSNs construct clusters, where a sensor node communicates with other nodes in its cluster, and a cluster head support connectivity between the sensor nodes and a sink node. In hybrid WSNs, cluster heads have cellular network interfaces for global connectivity. However, when WSNs are active and the load of cellular networks is high, the optimal assignment of cluster heads to base stations becomes critical. Therefore, in this paper, we propose a game theoretic model to find the optimal assignment of base stations for hybrid WSNs. Since the communication and energy cost is different according to cellular systems, we devise two game models for TDMA/FDMA and CDMA systems employing power prices to adapt to the varying efficiency of recent wireless technologies. The proposed model is defined on the assumptions of the ideal sensing field, but our evaluation shows that the proposed model is more adaptive and energy efficient than local selections. PMID:27589743

Heterogeneous Coupling between Interdependent Lattices Promotes the Cooperation in the Prisoner’s Dilemma Game

PubMed Central

Xia, Cheng-Yi; Meng, Xiao-Kun; Wang, Zhen

2015-01-01

In the research realm of game theory, interdependent networks have extended the content of spatial reciprocity, which needs the suitable coupling between networks. However, thus far, the vast majority of existing works just assume that the coupling strength between networks is symmetric. This hypothesis, to some extent, seems inconsistent with the ubiquitous observation of heterogeneity. Here, we study how the heterogeneous coupling strength, which characterizes the interdependency of utility between corresponding players of both networks, affects the evolution of cooperation in the prisoner’s dilemma game with two types of coupling schemes (symmetric and asymmetric ones). Compared with the traditional case, we show that heterogeneous coupling greatly promotes the collective cooperation. The symmetric scheme seems much better than the asymmetric case. Moreover, the role of varying amplitude of coupling strength is also studied on these two interdependent ways. Current findings are helpful for us to understand the evolution of cooperation within many real-world systems, in particular for the interconnected and interrelated systems. PMID:26102082

Analysis of Context Dependence in Social Interaction Networks of a Massively Multiplayer Online Role-Playing Game

PubMed Central

Son, Seokshin; Kang, Ah Reum; Kim, Hyun-chul; Kwon, Taekyoung; Park, Juyong; Kim, Huy Kang

2012-01-01

Rapid advances in modern computing and information technology have enabled millions of people to interact online via various social network and gaming services. The widespread adoption of such online services have made possible analysis of large-scale archival data containing detailed human interactions, presenting a very promising opportunity to understand the rich and complex human behavior. In collaboration with a leading global provider of Massively Multiplayer Online Role-Playing Games (MMORPGs), here we present a network science-based analysis of the interplay between distinct types of user interaction networks in the virtual world. We find that their properties depend critically on the nature of the context-interdependence of the interactions, highlighting the complex and multilayered nature of human interactions, a robust understanding of which we believe may prove instrumental in the designing of more realistic future virtual arenas as well as provide novel insights to the science of collective human behavior. PMID:22496771

Heterogeneous Coupling between Interdependent Lattices Promotes the Cooperation in the Prisoner's Dilemma Game.

PubMed

Xia, Cheng-Yi; Meng, Xiao-Kun; Wang, Zhen

2015-01-01

In the research realm of game theory, interdependent networks have extended the content of spatial reciprocity, which needs the suitable coupling between networks. However, thus far, the vast majority of existing works just assume that the coupling strength between networks is symmetric. This hypothesis, to some extent, seems inconsistent with the ubiquitous observation of heterogeneity. Here, we study how the heterogeneous coupling strength, which characterizes the interdependency of utility between corresponding players of both networks, affects the evolution of cooperation in the prisoner's dilemma game with two types of coupling schemes (symmetric and asymmetric ones). Compared with the traditional case, we show that heterogeneous coupling greatly promotes the collective cooperation. The symmetric scheme seems much better than the asymmetric case. Moreover, the role of varying amplitude of coupling strength is also studied on these two interdependent ways. Current findings are helpful for us to understand the evolution of cooperation within many real-world systems, in particular for the interconnected and interrelated systems.

Adaptive Multi-Agent Systems for Constrained Optimization

NASA Technical Reports Server (NTRS)

Macready, William; Bieniawski, Stefan; Wolpert, David H.

2004-01-01

Product Distribution (PD) theory is a new framework for analyzing and controlling distributed systems. Here we demonstrate its use for distributed stochastic optimization. First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (probability distribution of) the joint state of the agents. When the game in question is a team game with constraints, that equilibrium optimizes the expected value of the team game utility, subject to those constraints. The updating of the Lagrange parameters in the Lagrangian can be viewed as a form of automated annealing, that focuses the MAS more and more on the optimal pure strategy. This provides a simple way to map the solution of any constrained optimization problem onto the equilibrium of a Multi-Agent System (MAS). We present computer experiments involving both the Queen s problem and K-SAT validating the predictions of PD theory and its use for off-the-shelf distributed adaptive optimization.

Security Investment in Contagious Networks.

PubMed

Hasheminasab, Seyed Alireza; Tork Ladani, Behrouz

2018-01-16

Security of the systems is normally interdependent in such a way that security risks of one part affect other parts and threats spread through the vulnerable links in the network. So, the risks of the systems can be mitigated through investments in the security of interconnecting links. This article takes an innovative look at the problem of security investment of nodes on their vulnerable links in a given contagious network as a game-theoretic model that can be applied to a variety of applications including information systems. In the proposed game model, each node computes its corresponding risk based on the value of its assets, vulnerabilities, and threats to determine the optimum level of security investments on its external links respecting its limited budget. Furthermore, direct and indirect nonlinear influences of a node's security investment on the risks of other nodes are considered. The existence and uniqueness of the game's Nash equilibrium in the proposed game are also proved. Further analysis of the model in a practical case revealed that taking advantage of the investment effects of other players, perfectly rational players (i.e., those who use the utility function of the proposed game model) make more cost-effective decisions than selfish nonrational or semirational players. © 2018 Society for Risk Analysis.

Metabolic reconstruction, constraint-based analysis and game theory to probe genome-scale metabolic networks.

PubMed

Ruppin, Eytan; Papin, Jason A; de Figueiredo, Luis F; Schuster, Stefan

2010-08-01

With the advent of modern omics technologies, it has become feasible to reconstruct (quasi-) whole-cell metabolic networks and characterize them in more and more detail. Computer simulations of the dynamic behavior of such networks are difficult due to a lack of kinetic data and to computational limitations. In contrast, network analysis based on appropriate constraints such as the steady-state condition (constraint-based analysis) is feasible and allows one to derive conclusions about the system's metabolic capabilities. Here, we review methods for the reconstruction of metabolic networks, modeling techniques such as flux balance analysis and elementary flux modes and current progress in their development and applications. Game-theoretical methods for studying metabolic networks are discussed as well. Copyright © 2010 Elsevier Ltd. All rights reserved.

The Poisson model limits in NBA basketball: Complexity in team sports

NASA Astrophysics Data System (ADS)

Martín-González, Juan Manuel; de Saá Guerra, Yves; García-Manso, Juan Manuel; Arriaza, Enrique; Valverde-Estévez, Teresa

2016-12-01

Team sports are frequently studied by researchers. There is presumption that scoring in basketball is a random process and that can be described using the Poisson Model. Basketball is a collaboration-opposition sport, where the non-linear local interactions among players are reflected in the evolution of the score that ultimately determines the winner. In the NBA, the outcomes of close games are often decided in the last minute, where fouls play a main role. We examined 6130 NBA games in order to analyze the time intervals between baskets and scoring dynamics. Most numbers of baskets (n) over a time interval (ΔT) follow a Poisson distribution, but some (e.g., ΔT = 10 s, n > 3) behave as a Power Law. The Poisson distribution includes most baskets in any game, in most game situations, but in close games in the last minute, the numbers of events are distributed following a Power Law. The number of events can be adjusted by a mixture of two distributions. In close games, both teams try to maintain their advantage solely in order to reach the last minute: a completely different game. For this reason, we propose to use the Poisson model as a reference. The complex dynamics will emerge from the limits of this model.

Determinants of public cooperation in multiplex networks

NASA Astrophysics Data System (ADS)

Battiston, Federico; Perc, Matjaž; Latora, Vito

2017-07-01

Synergies between evolutionary game theory and statistical physics have significantly improved our understanding of public cooperation in structured populations. Multiplex networks, in particular, provide the theoretical framework within network science that allows us to mathematically describe the rich structure of interactions characterizing human societies. While research has shown that multiplex networks may enhance the resilience of cooperation, the interplay between the overlap in the structure of the layers and the control parameters of the corresponding games has not yet been investigated. With this aim, we consider here the public goods game on a multiplex network, and we unveil the role of the number of layers and the overlap of links, as well as the impact of different synergy factors in different layers, on the onset of cooperation. We show that enhanced public cooperation emerges only when a significant edge overlap is combined with at least one layer being able to sustain some cooperation by means of a sufficiently high synergy factor. In the absence of either of these conditions, the evolution of cooperation in multiplex networks is determined by the bounds of traditional network reciprocity with no enhanced resilience. These results caution against overly optimistic predictions that the presence of multiple social domains may in itself promote cooperation, and they help us better understand the complexity behind prosocial behavior in layered social systems.

Altered brain functional networks in people with Internet gaming disorder: Evidence from resting-state fMRI.

PubMed

Wang, Lingxiao; Wu, Lingdan; Lin, Xiao; Zhang, Yifen; Zhou, Hongli; Du, Xiaoxia; Dong, Guangheng

2016-08-30

Although numerous neuroimaging studies have detected structural and functional abnormality in specific brain regions and connections in subjects with Internet gaming disorder (IGD), the topological organization of the whole-brain network in IGD remain unclear. In this study, we applied graph theoretical analysis to explore the intrinsic topological properties of brain networks in Internet gaming disorder (IGD). 37 IGD subjects and 35 matched healthy control (HC) subjects underwent a resting-state functional magnetic resonance imaging scan. The functional networks were constructed by thresholding partial correlation matrices of 90 brain regions. Then we applied graph-based approaches to analysis their topological attributes, including small-worldness, nodal metrics, and efficiency. Both IGD and HC subjects show efficient and economic brain network, and small-world topology. Although there was no significant group difference in global topology metrics, the IGD subjects showed reduced regional centralities in the prefrontal cortex, left posterior cingulate cortex, right amygdala, and bilateral lingual gyrus, and increased functional connectivity in sensory-motor-related brain networks compared to the HC subjects. These results imply that people with IGD may be associated with functional network dysfunction, including impaired executive control and emotional management, but enhanced coordination among visual, sensorimotor, auditory and visuospatial systems. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Social games in a social network.

PubMed

Abramson, G; Kuperman, M

2001-03-01

We study an evolutionary version of the Prisoner's Dilemma game, played by agents placed in a small-world network. Agents are able to change their strategy, imitating that of the most successful neighbor. We observe that different topologies, ranging from regular lattices to random graphs, produce a variety of emergent behaviors. This is a contribution towards the study of social phenomena and transitions governed by the topology of the community.

Neural bases of selective attention in action video game players.

PubMed

Bavelier, D; Achtman, R L; Mani, M; Föcker, J

2012-05-15

Over the past few years, the very act of playing action video games has been shown to enhance several different aspects of visual selective attention, yet little is known about the neural mechanisms that mediate such attentional benefits. A review of the aspects of attention enhanced in action game players suggests there are changes in the mechanisms that control attention allocation and its efficiency (Hubert-Wallander, Green, & Bavelier, 2010). The present study used brain imaging to test this hypothesis by comparing attentional network recruitment and distractor processing in action gamers versus non-gamers as attentional demands increased. Moving distractors were found to elicit lesser activation of the visual motion-sensitive area (MT/MST) in gamers as compared to non-gamers, suggestive of a better early filtering of irrelevant information in gamers. As expected, a fronto-parietal network of areas showed greater recruitment as attentional demands increased in non-gamers. In contrast, gamers barely engaged this network as attentional demands increased. This reduced activity in the fronto-parietal network that is hypothesized to control the flexible allocation of top-down attention is compatible with the proposal that action game players may allocate attentional resources more automatically, possibly allowing more efficient early filtering of irrelevant information. Copyright © 2011 Elsevier Ltd. All rights reserved.

Using neural networks to model the behavior and decisions of gamblers, in particular, cyber-gamblers.

PubMed

Chan, Victor K Y

2010-03-01

This article describes the use of neural networks (a type of artificial intelligence) and an empirical data sample of, inter alia, the amounts of bets laid and the winnings/losses made in successive games by a number of cyber-gamblers to longitudinally model gamblers' behavior and decisions as to such bet amounts and the temporal trajectory of winnings/losses. The data was collected by videoing Texas Holdem gamblers at a cyber-gambling website. Six "persistent" gamblers were identified, totaling 675 games. The neural networks on average were able to predict bet amounts and cumulative winnings/losses in successive games accurately to three decimal places of the dollar. A more important conclusion is that the influence of a gambler's skills, strategies, and personality on his/her successive bet amounts and cumulative winnings/losses is almost totally reflected by the pattern(s) of his/her winnings/losses in the few initial games and his/her gambling account balance. This partially invalidates gamblers' illusions and fallacies that they can outperform others or even bankers. For government policy-makers, gambling industry operators, economists, sociologists, psychiatrists, and psychologists, this article provides models for gamblers' behavior and decisions. It also explores and exemplifies the usefulness of neural networks and artificial intelligence at large in the research on gambling.

Topological enslavement in evolutionary games on correlated multiplex networks

NASA Astrophysics Data System (ADS)

Kleineberg, Kaj-Kolja; Helbing, Dirk

2018-05-01

Governments and enterprises strongly rely on incentives to generate favorable outcomes from social and strategic interactions between individuals. The incentives are usually modeled by payoffs in evolutionary games, such as the prisoners dilemma or the harmony game, with imitation dynamics. Adjusting the incentives by changing the payoff parameters can favor cooperation, as found in the harmony game, over defection, which prevails in the prisoner’s dilemma. Here, we show that this is not always the case if individuals engage in strategic interactions in multiple domains. In particular, we investigate evolutionary games on multiplex networks where individuals obtain an aggregate payoff. We explicitly control the strength of degree correlations between nodes in the different layers of the multiplex. We find that if the multiplex is composed of many layers and degree correlations are strong, the topology of the system enslaves the dynamics and the final outcome, cooperation or defection, becomes independent of the payoff parameters. The fate of the system is then determined by the initial conditions.

Evolutionary games on graphs

NASA Astrophysics Data System (ADS)

Szabó, György; Fáth, Gábor

2007-07-01

Game theory is one of the key paradigms behind many scientific disciplines from biology to behavioral sciences to economics. In its evolutionary form and especially when the interacting agents are linked in a specific social network the underlying solution concepts and methods are very similar to those applied in non-equilibrium statistical physics. This review gives a tutorial-type overview of the field for physicists. The first four sections introduce the necessary background in classical and evolutionary game theory from the basic definitions to the most important results. The fifth section surveys the topological complications implied by non-mean-field-type social network structures in general. The next three sections discuss in detail the dynamic behavior of three prominent classes of models: the Prisoner's Dilemma, the Rock-Scissors-Paper game, and Competing Associations. The major theme of the review is in what sense and how the graph structure of interactions can modify and enrich the picture of long term behavioral patterns emerging in evolutionary games.

Real-time individualized training vectors for experiential learning.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Willis, Matt; Tucker, Eilish Marie; Raybourn, Elaine Marie

2011-01-01

Military training utilizing serious games or virtual worlds potentially generate data that can be mined to better understand how trainees learn in experiential exercises. Few data mining approaches for deployed military training games exist. Opportunities exist to collect and analyze these data, as well as to construct a full-history learner model. Outcomes discussed in the present document include results from a quasi-experimental research study on military game-based experiential learning, the deployment of an online game for training evidence collection, and results from a proof-of-concept pilot study on the development of individualized training vectors. This Lab Directed Research & Development (LDRD)more » project leveraged products within projects, such as Titan (Network Grand Challenge), Real-Time Feedback and Evaluation System, (America's Army Adaptive Thinking and Leadership, DARWARS Ambush! NK), and Dynamic Bayesian Networks to investigate whether machine learning capabilities could perform real-time, in-game similarity vectors of learner performance, toward adaptation of content delivery, and quantitative measurement of experiential learning.« less

On Location Learning: Authentic Applied Science with Networked Augmented Realities

NASA Astrophysics Data System (ADS)

Rosenbaum, Eric; Klopfer, Eric; Perry, Judy

2007-02-01

The learning of science can be made more like the practice of science through authentic simulated experiences. We have created a networked handheld Augmented Reality environment that combines the authentic role-playing of Augmented Realities and the underlying models of Participatory Simulations. This game, known as Outbreak @ The Institute, is played across a university campus where players take on the roles of doctors, medical technicians, and public health experts to contain a disease outbreak. Players can interact with virtual characters and employ virtual diagnostic tests and medicines. They are challenged to identify the source and prevent the spread of an infectious disease that can spread among real and/or virtual characters according to an underlying model. In this paper, we report on data from three high school classes who played the game. We investigate students' perception of the authenticity of the game in terms of their personal embodiment in the game, their experience playing different roles, and their understanding of the dynamic model underlying the game.

Public goods games on adaptive coevolutionary networks

NASA Astrophysics Data System (ADS)

Pichler, Elgar; Shapiro, Avi M.

2017-07-01

Productive societies feature high levels of cooperation and strong connections between individuals. Public Goods Games (PGGs) are frequently used to study the development of social connections and cooperative behavior in model societies. In such games, contributions to the public good are made only by cooperators, while all players, including defectors, reap public goods benefits, which are shares of the contributions amplified by a synergy factor. Classic results of game theory show that mutual defection, as opposed to cooperation, is the Nash Equilibrium of PGGs in well-mixed populations, where each player interacts with all others. In this paper, we explore the coevolutionary dynamics of a low information public goods game on a complex network in which players adapt to their environment in order to increase individual payoffs relative to past payoffs parameterized by greediness. Players adapt by changing their strategies, either to cooperate or to defect, and by altering their social connections. We find that even if players do not know other players' strategies and connectivity, cooperation can arise and persist despite large short-term fluctuations.

Public goods games on adaptive coevolutionary networks.

PubMed

Pichler, Elgar; Shapiro, Avi M

2017-07-01

Productive societies feature high levels of cooperation and strong connections between individuals. Public Goods Games (PGGs) are frequently used to study the development of social connections and cooperative behavior in model societies. In such games, contributions to the public good are made only by cooperators, while all players, including defectors, reap public goods benefits, which are shares of the contributions amplified by a synergy factor. Classic results of game theory show that mutual defection, as opposed to cooperation, is the Nash Equilibrium of PGGs in well-mixed populations, where each player interacts with all others. In this paper, we explore the coevolutionary dynamics of a low information public goods game on a complex network in which players adapt to their environment in order to increase individual payoffs relative to past payoffs parameterized by greediness. Players adapt by changing their strategies, either to cooperate or to defect, and by altering their social connections. We find that even if players do not know other players' strategies and connectivity, cooperation can arise and persist despite large short-term fluctuations.

A game theoretic algorithm to detect overlapping community structure in networks

NASA Astrophysics Data System (ADS)

Zhou, Xu; Zhao, Xiaohui; Liu, Yanheng; Sun, Geng

2018-04-01

Community detection can be used as an important technique for product and personalized service recommendation. A game theory based approach to detect overlapping community structure is introduced in this paper. The process of the community formation is converted into a game, when all agents (nodes) cannot improve their own utility, the game process will be terminated. The utility function is composed of a gain and a loss function and we present a new gain function in this paper. In addition, different from choosing action randomly among join, quit and switch for each agent to get new label, two new strategies for each agent to update its label are designed during the game, and the strategies are also evaluated and compared for each agent in order to find its best result. The overlapping community structure is naturally presented when the stop criterion is satisfied. The experimental results demonstrate that the proposed algorithm outperforms other similar algorithms for detecting overlapping communities in networks.

Understanding access and use of technology among youth with first-episode psychosis to inform the development of technology-enabled therapeutic interventions.

PubMed

Abdel-Baki, Amal; Lal, Shalini; D-Charron, Olivier; Stip, Emmanuel; Kara, Nadjia

2017-02-01

Computers, video games and technological devices are part of young people's everyday lives. However, their use in first-episode psychosis (FEP) treatment is rare. The purpose of this study was to better understand the access and use of technology among individuals with FEP, including gaming activities, to inform future development of technology-enabled therapeutic applications. Self-administered survey on use of technological tools in 71 FEP individuals. PCs/laptops were used by all participants; cellphones/smartphones by 92%, consoles by 83% (mainly male and younger participants). Women texted and used social networks more frequently; men played games (mainly action) more often. The younger individuals reported playing games frequently (32% daily) with less use of the Web and social networks (favourite: Facebook). These data will be useful for developing Web-based psychoeducation tools and cognitive remediation video games for youth with FEP. © 2015 Wiley Publishing Asia Pty Ltd.

Why to Limit Your Child's Media Use

MedlinePlus

... families) own a device used to play video games . Why Limit Media Use? Overuse of digital media ... social networking, chat rooms, e-mail, and online games to contact and exploit children. Cyberbullying . Children and ...

A game-theoretical approach to multimedia social networks security.

PubMed

Liu, Enqiang; Liu, Zengliang; Shao, Fei; Zhang, Zhiyong

2014-01-01

The contents access and sharing in multimedia social networks (MSNs) mainly rely on access control models and mechanisms. Simple adoptions of security policies in the traditional access control model cannot effectively establish a trust relationship among parties. This paper proposed a novel two-party trust architecture (TPTA) to apply in a generic MSN scenario. According to the architecture, security policies are adopted through game-theoretic analyses and decisions. Based on formalized utilities of security policies and security rules, the choice of security policies in content access is described as a game between the content provider and the content requester. By the game method for the combination of security policies utility and its influences on each party's benefits, the Nash equilibrium is achieved, that is, an optimal and stable combination of security policies, to establish and enhance trust among stakeholders.

A Game-Theoretical Approach to Multimedia Social Networks Security

PubMed Central

Liu, Enqiang; Liu, Zengliang; Shao, Fei; Zhang, Zhiyong

2014-01-01

The contents access and sharing in multimedia social networks (MSNs) mainly rely on access control models and mechanisms. Simple adoptions of security policies in the traditional access control model cannot effectively establish a trust relationship among parties. This paper proposed a novel two-party trust architecture (TPTA) to apply in a generic MSN scenario. According to the architecture, security policies are adopted through game-theoretic analyses and decisions. Based on formalized utilities of security policies and security rules, the choice of security policies in content access is described as a game between the content provider and the content requester. By the game method for the combination of security policies utility and its influences on each party's benefits, the Nash equilibrium is achieved, that is, an optimal and stable combination of security policies, to establish and enhance trust among stakeholders. PMID:24977226

Wellness partners: design and evaluation of a web-based physical activity diary with social gaming features for adults.

PubMed

Gotsis, Marientina; Wang, Hua; Spruijt-Metz, Donna; Jordan-Marsh, Maryalice; Valente, Thomas William

2013-02-01

The United States is currently in an age of obesity and inactivity despite increasing public awareness and scientific knowledge of detrimental long-term health effects of this lifestyle. Behavior-tracking diaries offer an effective strategy for physical activity adherence and weight management. Furthermore, Web-based physical activity diaries can engage meaningful partners in people's social networks through fun online gaming interactions and generate motivational mechanisms for effective behavioral change and positive health outcomes. Wellness Partners (WP) is a Web-based intervention in the form of a physical activity diary with social networking and game features. Two versions were designed and developed for the purpose of this study-"Diary" only and "Diary+Game". The objectives of this study included pilot testing the research process of this intervention design, implementation, evaluation, and exploring the effectiveness of social gaming features on adult participants' physical activity and anthropometric measures. We conducted a field experiment with randomized crossover design. Assessments occurred at baseline, first follow-up (FU, 5-8 weeks after using one version of WP), and second FU (5-8 weeks of using the other version of WP). In the control condition, participants started with the "Diary" version of WP while in the experimental condition, participants started with the "Diary+Game" version of WP. A total of 54 adults (egos) ages 44-88, and their family and friends (alters) ages 17-69 participated in the study in ego-network groups. Both egos and their alters completed online surveys about their exercise habits. In addition, egos completed anthropometric measurements of BMI, fat percentage, and fat mass by bioimpedance. From October 2009 to May 2010, flyers, emails, and Web advertisements yielded 335 volunteers who were screened. Rolling recruitment resulted in enrollment of 142 qualified participants in 54 ego-network groups, which were randomly assigned to a study condition. The final analytic sample included 87 individuals from 41 groups. Data were collected from December 2009 to August 2010, and data analysis was completed in 2011. Overall, the participants were given access to the intervention for 10-13 weeks. Statistical analysis suggested an increase in self-reported exercise frequency (mean days per week) from baseline (2.57, SD 1.92) to first FU (3.21, SD 1.74) in both conditions. Stronger effects were seen in the condition where Diary+Game was played first, especially in network groups with larger age variation between the alters and egos. Overall, the decrease in egos' BMI was statistically significant from baseline to first FU, with greater decrease for those in the Diary+Game first condition (-0.26 vs -0.16 in the Diary first condition). The Wellness Partners program increased physical activity among participants and resulted in health benefits among the egos. Web-based diary interventions designed with social gaming features hold potential to promote active lifestyles for middle-age adults and people in their social networks.

Stable producer–scrounger dynamics in wild birds: sociability and learning speed covary with scrounging behaviour

PubMed Central

Morand-Ferron, J.

2017-01-01

There has been extensive game-theoretic modelling of conditions leading to equilibria of producer–scrounger dichotomies in groups. However there is a surprising paucity of experimental evidence in wild populations. Here, we examine producer–scrounger games in five subpopulations of birds feeding at a socially learnt foraging task. Over four weeks, a bimodal distribution of producers and scroungers emerged in all areas, with pronounced and consistent individual tactic specialization persisting over 3 years. Tactics were unrelated to exploratory personality, but correlated with latency to contact and learn the foraging task, with the late arrivers and slower learners more likely to adopt the scrounging role. Additionally, the social environment was also important: at the broad scale, larger subpopulations with a higher social density contained proportionally more scroungers, while within subpopulations scroungers tended to be central in the social network and be observed in larger foraging flocks. This study thus provides a rare example of a stable, dimorphic distribution of producer–scrounger tactics in a wild population. It further gives support across multiple scales for a major prediction of social foraging theory; that the frequency of scroungers increases with group size. PMID:28404775

Stable producer-scrounger dynamics in wild birds: sociability and learning speed covary with scrounging behaviour.

PubMed

Aplin, L M; Morand-Ferron, J

2017-04-12

There has been extensive game-theoretic modelling of conditions leading to equilibria of producer-scrounger dichotomies in groups. However there is a surprising paucity of experimental evidence in wild populations. Here, we examine producer-scrounger games in five subpopulations of birds feeding at a socially learnt foraging task. Over four weeks, a bimodal distribution of producers and scroungers emerged in all areas, with pronounced and consistent individual tactic specialization persisting over 3 years. Tactics were unrelated to exploratory personality, but correlated with latency to contact and learn the foraging task, with the late arrivers and slower learners more likely to adopt the scrounging role. Additionally, the social environment was also important: at the broad scale, larger subpopulations with a higher social density contained proportionally more scroungers, while within subpopulations scroungers tended to be central in the social network and be observed in larger foraging flocks. This study thus provides a rare example of a stable, dimorphic distribution of producer-scrounger tactics in a wild population. It further gives support across multiple scales for a major prediction of social foraging theory; that the frequency of scroungers increases with group size. © 2017 The Authors.

Game-theoretic strategies for asymmetric networked systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rao, Nageswara S.; Ma, Chris Y. T.; Hausken, Kjell

Abstract—We consider an infrastructure consisting of a network of systems each composed of discrete components that can be reinforced at a certain cost to guard against attacks. The network provides the vital connectivity between systems, and hence plays a critical, asymmetric role in the infrastructure operations. We characterize the system-level correlations using the aggregate failure correlation function that specifies the infrastructure failure probability given the failure of an individual system or network. The survival probabilities of systems and network satisfy first-order differential conditions that capture the component-level correlations. We formulate the problem of ensuring the infrastructure survival as a gamemore » between anattacker and a provider, using the sum-form and product-form utility functions, each composed of a survival probability term and a cost term. We derive Nash Equilibrium conditions which provide expressions for individual system survival probabilities, and also the expected capacity specified by the total number of operational components. These expressions differ only in a single term for the sum-form and product-form utilities, despite their significant differences.We apply these results to simplified models of distributed cloud computing infrastructures.« less

An Evolutionary Game Theory Model of Spontaneous Brain Functioning.

PubMed

Madeo, Dario; Talarico, Agostino; Pascual-Leone, Alvaro; Mocenni, Chiara; Santarnecchi, Emiliano

2017-11-22

Our brain is a complex system of interconnected regions spontaneously organized into distinct networks. The integration of information between and within these networks is a continuous process that can be observed even when the brain is at rest, i.e. not engaged in any particular task. Moreover, such spontaneous dynamics show predictive value over individual cognitive profile and constitute a potential marker in neurological and psychiatric conditions, making its understanding of fundamental importance in modern neuroscience. Here we present a theoretical and mathematical model based on an extension of evolutionary game theory on networks (EGN), able to capture brain's interregional dynamics by balancing emulative and non-emulative attitudes among brain regions. This results in the net behavior of nodes composing resting-state networks identified using functional magnetic resonance imaging (fMRI), determining their moment-to-moment level of activation and inhibition as expressed by positive and negative shifts in BOLD fMRI signal. By spontaneously generating low-frequency oscillatory behaviors, the EGN model is able to mimic functional connectivity dynamics, approximate fMRI time series on the basis of initial subset of available data, as well as simulate the impact of network lesions and provide evidence of compensation mechanisms across networks. Results suggest evolutionary game theory on networks as a new potential framework for the understanding of human brain network dynamics.

Nanoscale molecular communication networks: a game-theoretic perspective

NASA Astrophysics Data System (ADS)

Jiang, Chunxiao; Chen, Yan; Ray Liu, K. J.

2015-12-01

Currently, communication between nanomachines is an important topic for the development of novel devices. To implement a nanocommunication system, diffusion-based molecular communication is considered as a promising bio-inspired approach. Various technical issues about molecular communications, including channel capacity, noise and interference, and modulation and coding, have been studied in the literature, while the resource allocation problem among multiple nanomachines has not been well investigated, which is a very important issue since all the nanomachines share the same propagation medium. Considering the limited computation capability of nanomachines and the expensive information exchange cost among them, in this paper, we propose a game-theoretic framework for distributed resource allocation in nanoscale molecular communication systems. We first analyze the inter-symbol and inter-user interference, as well as bit error rate performance, in the molecular communication system. Based on the interference analysis, we formulate the resource allocation problem as a non-cooperative molecule emission control game, where the Nash equilibrium is found and proved to be unique. In order to improve the system efficiency while guaranteeing fairness, we further model the resource allocation problem using a cooperative game based on the Nash bargaining solution, which is proved to be proportionally fair. Simulation results show that the Nash bargaining solution can effectively ensure fairness among multiple nanomachines while achieving comparable social welfare performance with the centralized scheme.

Analysis of the expected density of internal equilibria in random evolutionary multi-player multi-strategy games.

PubMed

Duong, Manh Hong; Han, The Anh

2016-12-01

In this paper, we study the distribution and behaviour of internal equilibria in a d-player n-strategy random evolutionary game where the game payoff matrix is generated from normal distributions. The study of this paper reveals and exploits interesting connections between evolutionary game theory and random polynomial theory. The main contributions of the paper are some qualitative and quantitative results on the expected density, [Formula: see text], and the expected number, E(n, d), of (stable) internal equilibria. Firstly, we show that in multi-player two-strategy games, they behave asymptotically as [Formula: see text] as d is sufficiently large. Secondly, we prove that they are monotone functions of d. We also make a conjecture for games with more than two strategies. Thirdly, we provide numerical simulations for our analytical results and to support the conjecture. As consequences of our analysis, some qualitative and quantitative results on the distribution of zeros of a random Bernstein polynomial are also obtained.

Cyber security issues in online games

NASA Astrophysics Data System (ADS)

Zhao, Chen

2018-04-01

With the rapid development of the Internet, online gaming has become a way of entertainment for many young people in the modern era. However, in recent years, cyber security issues in online games have emerged in an endless stream, which have also caused great attention of many game operators. Common cyber security problems in the game include information disclosure and cyber-attacks. These problems will directly or indirectly cause economic losses to gamers. Many gaming companies are enhancing the stability and security of their network or gaming systems in order to enhance the gaming user experience. This article has carried out the research of the cyber security issues in online games by introducing the background and some common cyber security threats, and by proposing the latent solution. Finally, it speculates the future research direction of the cyber security issues of online games in the hope of providing feasible solution and useful information for game operators.

Distribution strategy of energy supply chain based on corporate social responsibility

NASA Astrophysics Data System (ADS)

Song, Qiaona

2018-02-01

From corporate social responsibilities influence on the consumer`s preferences, applying the basic Idea of game theory, the study on tactics of profit distribution of the one-period game between manufacturer and vendor in energy supply chain,then the repetitive game results of the two partners are discussed. The results show that alliance pricing is the unique nash equilibrium of the one-period game between manufacturer and vendor,and the expect profit of both manufacturer and vendor will increase after cooperation in the range of agreed value of the profit distribution factor. It`s optimal for manufacturer and vendor to insist on alliance pricing for their long-term benefits in energy supply chain.

Demonstrating the Effect of Supply Chain Disruptions through an Online Beer Distribution Game

ERIC Educational Resources Information Center

Sarkar, Sourish; Kumar, Sanjay

2016-01-01

This article describes a classroom tool to teach the impact of supply chain disruptions and mitigation strategies based on information sharing and collaboration. The tool is an adaptation of the Beer Distribution Game, is easy to play, and can be hosted online or on local servers. The game considers several scenarios based on the location of the…

A Methodology to Assess UrbanSim Scenarios

DTIC Science & Technology

2012-09-01

Education LOE – Line of Effort MMOG – Massively Multiplayer Online Game MC3 – Maneuver Captain’s Career Course MSCCC – Maneuver Support...augmented reality simulations, increased automation and artificial intelligence simulation, and massively multiplayer online games (MMOG), among...distribution is unlimited 12b. DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words) Turn-based strategy games and simulations are vital tools for military

Learning consensus in adversarial environments

NASA Astrophysics Data System (ADS)

Vamvoudakis, Kyriakos G.; García Carrillo, Luis R.; Hespanha, João. P.

2013-05-01

This work presents a game theory-based consensus problem for leaderless multi-agent systems in the presence of adversarial inputs that are introducing disturbance to the dynamics. Given the presence of enemy components and the possibility of malicious cyber attacks compromising the security of networked teams, a position agreement must be reached by the networked mobile team based on environmental changes. The problem is addressed under a distributed decision making framework that is robust to possible cyber attacks, which has an advantage over centralized decision making in the sense that a decision maker is not required to access information from all the other decision makers. The proposed framework derives three tuning laws for every agent; one associated with the cost, one associated with the controller, and one with the adversarial input.

A Quantum Shuffling Game for Teaching Statistical Mechanics

ERIC Educational Resources Information Center

Black, P. J.; And Others

1971-01-01

A game simulating an Einstein model of a crystal producing a Boltzmann distribution. Computer-made films present the results with large distributions showing heat flow and some applications to entropy. (TS)

Quantum Game of Life

NASA Astrophysics Data System (ADS)

Glick, Aaron; Carr, Lincoln; Calarco, Tommaso; Montangero, Simone

2014-03-01

In order to investigate the emergence of complexity in quantum systems, we present a quantum game of life, inspired by Conway's classic game of life. Through Matrix Product State (MPS) calculations, we simulate the evolution of quantum systems, dictated by a Hamiltonian that defines the rules of our quantum game. We analyze the system through a number of measures which elicit the emergence of complexity in terms of spatial organization, system dynamics, and non-local mutual information within the network. Funded by NSF

Real-time strategy video game experience and structural connectivity - A diffusion tensor imaging study.

PubMed

Kowalczyk, Natalia; Shi, Feng; Magnuski, Mikolaj; Skorko, Maciek; Dobrowolski, Pawel; Kossowski, Bartosz; Marchewka, Artur; Bielecki, Maksymilian; Kossut, Malgorzata; Brzezicka, Aneta

2018-06-20

Experienced video game players exhibit superior performance in visuospatial cognition when compared to non-players. However, very little is known about the relation between video game experience and structural brain plasticity. To address this issue, a direct comparison of the white matter brain structure in RTS (real time strategy) video game players (VGPs) and non-players (NVGPs) was performed. We hypothesized that RTS experience can enhance connectivity within and between occipital and parietal regions, as these regions are likely to be involved in the spatial and visual abilities that are trained while playing RTS games. The possible influence of long-term RTS game play experience on brain structural connections was investigated using diffusion tensor imaging (DTI) and a region of interest (ROI) approach in order to describe the experience-related plasticity of white matter. Our results revealed significantly more total white matter connections between occipital and parietal areas and within occipital areas in RTS players compared to NVGPs. Additionally, the RTS group had an altered topological organization of their structural network, expressed in local efficiency within the occipito-parietal subnetwork. Furthermore, the positive association between network metrics and time spent playing RTS games suggests a close relationship between extensive, long-term RTS game play and neuroplastic changes. These results indicate that long-term and extensive RTS game experience induces alterations along axons that link structures of the occipito-parietal loop involved in spatial and visual processing. © 2018 Wiley Periodicals, Inc.

Approximation of Nash equilibria and the network community structure detection problem

PubMed Central

2017-01-01

Game theory based methods designed to solve the problem of community structure detection in complex networks have emerged in recent years as an alternative to classical and optimization based approaches. The Mixed Nash Extremal Optimization uses a generative relation for the characterization of Nash equilibria to identify the community structure of a network by converting the problem into a non-cooperative game. This paper proposes a method to enhance this algorithm by reducing the number of payoff function evaluations. Numerical experiments performed on synthetic and real-world networks show that this approach is efficient, with results better or just as good as other state-of-the-art methods. PMID:28467496

Chimera states in a network-organized public goods game with destructive agents

NASA Astrophysics Data System (ADS)

Kouvaris, Nikos E.; Requejo, Rubén J.; Hizanidis, Johanne; Díaz-Guilera, Albert

2016-12-01

We found that a network-organized metapopulation of cooperators, defectors, and destructive agents playing the public goods game with mutations can collectively reach global synchronization or chimera states. Global synchronization is accompanied by a collective periodic burst of cooperation, whereas chimera states reflect the tendency of the networked metapopulation to be fragmented in clusters of synchronous and incoherent bursts of cooperation. Numerical simulations have shown that the system's dynamics switches between these two steady states through a first order transition. Depending on the parameters determining the dynamical and topological properties, chimera states with different numbers of coherent and incoherent clusters are observed. Our results present the first systematic study of chimera states and their characterization in the context of evolutionary game theory. This provides a valuable insight into the details of their occurrence, extending the relevance of such states to natural and social systems.

Stochastic Online Learning in Dynamic Networks under Unknown Models

DTIC Science & Technology

2016-08-02

Repeated Game with Incomplete Information, IEEE International Conference on Acoustics, Speech, and Signal Processing. 20-MAR-16, Shanghai, China...in a game theoretic framework for the application of multi-seller dynamic pricing with unknown demand models. We formulated the problem as an...infinitely repeated game with incomplete information and developed a dynamic pricing strategy referred to as Competitive and Cooperative Demand Learning

Math Around the World: Grades 5-8. Teachers' Guide. Great Explorations in Math and Science (GEMS).

ERIC Educational Resources Information Center

Braxton, Beverly; And Others

This document is a collection of eight games from four continents. Students use mathematics that is directly relevant to them as they take part in the games. The first five games (NIM, Kalah, Tower of Hanoi, Shongo Networks, and Magic Squares) feature presentation instructions that describe multiple-session classroom activities for grades 5-8.…

Robust synthetic biology design: stochastic game theory approach.

PubMed

Chen, Bor-Sen; Chang, Chia-Hung; Lee, Hsiao-Ching

2009-07-15

Synthetic biology is to engineer artificial biological systems to investigate natural biological phenomena and for a variety of applications. However, the development of synthetic gene networks is still difficult and most newly created gene networks are non-functioning due to uncertain initial conditions and disturbances of extra-cellular environments on the host cell. At present, how to design a robust synthetic gene network to work properly under these uncertain factors is the most important topic of synthetic biology. A robust regulation design is proposed for a stochastic synthetic gene network to achieve the prescribed steady states under these uncertain factors from the minimax regulation perspective. This minimax regulation design problem can be transformed to an equivalent stochastic game problem. Since it is not easy to solve the robust regulation design problem of synthetic gene networks by non-linear stochastic game method directly, the Takagi-Sugeno (T-S) fuzzy model is proposed to approximate the non-linear synthetic gene network via the linear matrix inequality (LMI) technique through the Robust Control Toolbox in Matlab. Finally, an in silico example is given to illustrate the design procedure and to confirm the efficiency and efficacy of the proposed robust gene design method. http://www.ee.nthu.edu.tw/bschen/SyntheticBioDesign_supplement.pdf.

Competitive game theoretic optimal routing in optical networks

NASA Astrophysics Data System (ADS)

Yassine, Abdulsalam; Kabranov, Ognian; Makrakis, Dimitrios

2002-09-01

Optical transport service providers need control and optimization strategies for wavelength management, network provisioning, restoration and protection, allowing them to define and deploy new services and maintain competitiveness. In this paper, we investigate a game theory based model for wavelength and flow assignment in multi wavelength optical networks, consisting of several backbone long-haul optical network transport service providers (TSPs) who are offering their services -in terms of bandwidth- to Internet service providers (ISPs). The ISPs act as brokers or agents between the TSP and end user. The agent (ISP) buys services (bandwidth) from the TSP. The TSPs compete among themselves to sell their services and maintain profitability. We present a case study, demonstrating the impact of different bandwidth broker demands on the supplier's profit and the price paid by the network broker.

A CyberCIEGE Scenario Illustrating Secrecy Issues in an Internal Corporate Network Connected to the Internet

DTIC Science & Technology

2004-09-01

to provide access to and protect are the NG Game Code, Employee Files, E -MAIL, Marketing Plans and Legacy Code. The NG Game Code is the MOST...major hit. E -MAIL is classified NON- SENSITIVE. The Marketing Plans are for the NG Game Code. They contain information concerning what the new...simulation games currently on the market except that, rather than allowing players to choose rides, refreshments and facilities, CyberCIEGE will

Game-theoretic homological sensor resource management for SSA

NASA Astrophysics Data System (ADS)

Chin, Sang Peter

2009-05-01

We present a game-theoretic approach to Level 2/3/4 fusion for the purpose of Space Situational Awareness (SSA) along with prototypical SW implementation of this approach to demonstrate its effectiveness for possible future space operations. Our approach is based upon innovative techniques that we are developing to solve dynamic games and Nperson cooperative/non-cooperative games, as well as a new emerging homological sensing algorithms which we apply to control disparate network of space sensors in order to gain better SSA.

Interweaving interactions in virtual worlds: a case study.

PubMed

Cantamesse, Matteo; Galimberti, Carlo; Giacoma, Gianandrea

2011-01-01

The aim of this study was to examine the effect of playing the online game World of Warcraft (WoW), both on adolescent's (effective) social interaction and on the competence they developed on it. Social interactions within the game environment have been investigated by integrating qualitative and quantitative methods: conversation analysis and social network analysis (SNA). From a psychosocial point of view, the in-game interactions, and in particular conversational exchanges, turn out to be a collaborative path of the joint definition of identities and social ties, with reflection on in-game processes and out-game relationship.

The co-evolution of networks and prisoner’s dilemma game by considering sensitivity and visibility

NASA Astrophysics Data System (ADS)

Li, Dandan; Ma, Jing; Han, Dun; Sun, Mei; Tian, Lixin; Stanley, H. Eugene

2017-03-01

Strategies adopted by individuals in a social network significantly impact the network, and they strongly affect relationships between individuals in the network. Links between individuals also heavily influence their levels of cooperation. Taking into account the evolution of each individual’s connection, we explore how sensitivity and visibility affect the prisoner’s dilemma game. The so-called ‘sensitivity’ and ‘visibility’ respectively present one’s self-protection consciousness and the ability of gaining information. We find that at moderate levels of player sensitivity cooperative behavior increases, but that at high levels it is inhibited. We also find that the heterogeneity of the weight of individuals at the end of the game is higher when sensitivity and visibility are increased, but that the successful-defection-payoff has less impact on the weight of individuals and on the relationship between the heterogeneity of the weight of individuals and the density of cooperators. This framework can be used to clarify the interaction mechanism between the micro-level of individual behavior and the macro-level of individual co-evolutionary processes.

The co-evolution of networks and prisoner's dilemma game by considering sensitivity and visibility.

PubMed

Li, Dandan; Ma, Jing; Han, Dun; Sun, Mei; Tian, Lixin; Stanley, H Eugene

2017-03-24

Strategies adopted by individuals in a social network significantly impact the network, and they strongly affect relationships between individuals in the network. Links between individuals also heavily influence their levels of cooperation. Taking into account the evolution of each individual's connection, we explore how sensitivity and visibility affect the prisoner's dilemma game. The so-called 'sensitivity' and 'visibility' respectively present one's self-protection consciousness and the ability of gaining information. We find that at moderate levels of player sensitivity cooperative behavior increases, but that at high levels it is inhibited. We also find that the heterogeneity of the weight of individuals at the end of the game is higher when sensitivity and visibility are increased, but that the successful-defection-payoff has less impact on the weight of individuals and on the relationship between the heterogeneity of the weight of individuals and the density of cooperators. This framework can be used to clarify the interaction mechanism between the micro-level of individual behavior and the macro-level of individual co-evolutionary processes.

The co-evolution of networks and prisoner’s dilemma game by considering sensitivity and visibility

PubMed Central

Li, Dandan; Ma, Jing; Han, Dun; Sun, Mei; Tian, Lixin; Stanley, H. Eugene

2017-01-01

Strategies adopted by individuals in a social network significantly impact the network, and they strongly affect relationships between individuals in the network. Links between individuals also heavily influence their levels of cooperation. Taking into account the evolution of each individual’s connection, we explore how sensitivity and visibility affect the prisoner’s dilemma game. The so-called ‘sensitivity’ and ‘visibility’ respectively present one’s self-protection consciousness and the ability of gaining information. We find that at moderate levels of player sensitivity cooperative behavior increases, but that at high levels it is inhibited. We also find that the heterogeneity of the weight of individuals at the end of the game is higher when sensitivity and visibility are increased, but that the successful-defection-payoff has less impact on the weight of individuals and on the relationship between the heterogeneity of the weight of individuals and the density of cooperators. This framework can be used to clarify the interaction mechanism between the micro-level of individual behavior and the macro-level of individual co-evolutionary processes. PMID:28338070

Naming game with biased assimilation over adaptive networks

NASA Astrophysics Data System (ADS)

Fu, Guiyuan; Zhang, Weidong

2018-01-01

The dynamics of two-word naming game incorporating the influence of biased assimilation over adaptive network is investigated in this paper. Firstly an extended naming game with biased assimilation (NGBA) is proposed. The hearer in NGBA accepts the received information in a biased manner, where he may refuse to accept the conveyed word from the speaker with a predefined probability, if the conveyed word is different from his current memory. Secondly, the adaptive network is formulated by rewiring the links. Theoretical analysis is developed to show that the population in NGBA will eventually reach global consensus on either A or B. Numerical simulation results show that the larger strength of biased assimilation on both words, the slower convergence speed, while larger strength of biased assimilation on only one word can slightly accelerate the convergence; larger population size can make the rate of convergence slower to a large extent when it increases from a relatively small size, while such effect becomes minor when the population size is large; the behavior of adaptively reconnecting the existing links can greatly accelerate the rate of convergence especially on the sparse connected network.

Evolutionary prisoner's dilemma games on the network with punishment and opportunistic partner switching

NASA Astrophysics Data System (ADS)

Takesue, H.

2018-02-01

Punishment and partner switching are two well-studied mechanisms that support the evolution of cooperation. Observation of human behaviour suggests that the extent to which punishment is adopted depends on the usage of alternative mechanisms, including partner switching. In this study, we investigate the combined effect of punishment and partner switching in evolutionary prisoner's dilemma games conducted on a network. In the model, agents are located on the network and participate in the prisoner's dilemma games with punishment. In addition, they can opportunistically switch interaction partners to improve their payoff. Our Monte Carlo simulation showed that a large frequency of punishers is required to suppress defectors when the frequency of partner switching is low. In contrast, cooperation is the most abundant strategy when the frequency of partner switching is high regardless of the strength of punishment. Interestingly, cooperators become abundant not because they avoid the cost of inflicting punishment and earn a larger average payoff per game but rather because they have more numerous opportunities to be referred to as a role agent by defectors. Our results imply that the fluidity of social relationships has a profound effect on the adopted strategy in maintaining cooperation.

The Identity Mapping Project: Demographic differences in patterns of distributed identity.

PubMed

Gilbert, Richard L; Dionisio, John David N; Forney, Andrew; Dorin, Philip

2015-01-01

The advent of cloud computing and a multi-platform digital environment is giving rise to a new phase of human identity called "The Distributed Self." In this conception, aspects of the self are distributed into a variety of 2D and 3D digital personas with the capacity to reflect any number of combinations of now malleable personality traits. In this way, the source of human identity remains internal and embodied, but the expression or enactment of the self becomes increasingly external, disembodied, and distributed on demand. The Identity Mapping Project (IMP) is an interdisciplinary collaboration between psychology and computer Science designed to empirically investigate the development of distributed forms of identity. Methodologically, it collects a large database of "identity maps" - computerized graphical representations of how active someone is online and how their identity is expressed and distributed across 7 core digital domains: email, blogs/personal websites, social networks, online forums, online dating sites, character based digital games, and virtual worlds. The current paper reports on gender and age differences in online identity based on an initial database of distributed identity profiles.

RELM: developing a serious game to teach evidence-based medicine in an academic health sciences setting.

PubMed

Gleason, Ann Whitney

2015-01-01

Gaming as a means of delivering online education continues to gain in popularity. Online games provide an engaging and enjoyable way of learning. Gaming is especially appropriate for case-based teaching, and provides a conducive environment for adult independent learning. With funding from the National Network of Libraries of Medicine, Pacific Northwest Region (NN/LM PNR), the University of Washington (UW) Health Sciences Library, and the UW School of Medicine are collaborating to create an interactive, self-paced online game that teaches players to employ the steps in practicing evidence-based medicine. The game encourages life-long learning and literacy skills and could be used for providing continuing medical education.

Zoning Issues and Area of Interest Management in Massively Multiplayer Online Games

NASA Astrophysics Data System (ADS)

Ahmed, Dewan Tanvir; Shirmohammadi, Shervin

Game is a way of entertainment, a means for excitement, fun and socialization. Online games have achieved popularity due to increasing broadband adoption among consumers. Relatively cheap bandwidth Internet connections allow large number of players to play together. Since the introduction of Network Virtual Environment (NVE) in 1980s for military simulation, many interesting applications have been evolved over the past few decades. Massively multiplayer online (role-playing) game, MMOG or MMORPG, is a new genre of online games that has emerged with the introduction of Ultima since 1997. It is a kind of online computer game with the participation of hundreds of thousands of players in a virtual world.

Finite-horizon differential games for missile-target interception system using adaptive dynamic programming with input constraints

NASA Astrophysics Data System (ADS)

Sun, Jingliang; Liu, Chunsheng

2018-01-01

In this paper, the problem of intercepting a manoeuvring target within a fixed final time is posed in a non-linear constrained zero-sum differential game framework. The Nash equilibrium solution is found by solving the finite-horizon constrained differential game problem via adaptive dynamic programming technique. Besides, a suitable non-quadratic functional is utilised to encode the control constraints into a differential game problem. The single critic network with constant weights and time-varying activation functions is constructed to approximate the solution of associated time-varying Hamilton-Jacobi-Isaacs equation online. To properly satisfy the terminal constraint, an additional error term is incorporated in a novel weight-updating law such that the terminal constraint error is also minimised over time. By utilising Lyapunov's direct method, the closed-loop differential game system and the estimation weight error of the critic network are proved to be uniformly ultimately bounded. Finally, the effectiveness of the proposed method is demonstrated by using a simple non-linear system and a non-linear missile-target interception system, assuming first-order dynamics for the interceptor and target.

Hierarchical Task Network Prototyping In Unity3d

DTIC Science & Technology

2016-06-01

visually debug. Here we present a solution for prototyping HTNs by extending an existing commercial implementation of Behavior Trees within the Unity3D game ...HTN, dynamic behaviors, behavior prototyping, agent-based simulation, entity-level combat model, game engine, discrete event simulation, virtual...commercial implementation of Behavior Trees within the Unity3D game engine prior to building the HTN in COMBATXXI. Existing HTNs were emulated within

Playing the Game and Speaking the Right Language: Language Policy and Materiality in a Bilingual Preschool Activity

ERIC Educational Resources Information Center

Martín-Bylund, Anna

2017-01-01

What are the material-semiotic relationships between a language policy and a table game activity in a bilingual preschool? Using Actor-Network Theory (ANT), the aim of this article is to explore this question, working with both human and nonhuman aspects of the activity, symmetrically, at the same level. The game playing activity takes place at a…

Heterogeneous network promotes species coexistence: metapopulation model for rock-paper-scissors game.

PubMed

Nagatani, Takashi; Ichinose, Genki; Tainaka, Kei-Ichi

2018-05-04

Understanding mechanisms of biodiversity has been a central question in ecology. The coexistence of three species in rock-paper-scissors (RPS) systems are discussed by many authors; however, the relation between coexistence and network structure is rarely discussed. Here we present a metapopulation model for RPS game. The total population is assumed to consist of three subpopulations (nodes). Each individual migrates by random walk; the destination of migration is randomly determined. From reaction-migration equations, we obtain the population dynamics. It is found that the dynamic highly depends on network structures. When a network is homogeneous, the dynamics are neutrally stable: each node has a periodic solution, and the oscillations synchronize in all nodes. However, when a network is heterogeneous, the dynamics approach stable focus and all nodes reach equilibriums with different densities. Hence, the heterogeneity of the network promotes biodiversity.

Dependency links can hinder the evolution of cooperation in the prisoner's dilemma game on lattices and networks.

PubMed

Wang, Xuwen; Nie, Sen; Wang, Binghong

2015-01-01

Networks with dependency links are more vulnerable when facing the attacks. Recent research also has demonstrated that the interdependent groups support the spreading of cooperation. We study the prisoner's dilemma games on spatial networks with dependency links, in which a fraction of individual pairs is selected to depend on each other. The dependency individuals can gain an extra payoff whose value is between the payoff of mutual cooperation and the value of temptation to defect. Thus, this mechanism reflects that the dependency relation is stronger than the relation of ordinary mutual cooperation, but it is not large enough to cause the defection of the dependency pair. We show that the dependence of individuals hinders, promotes and never affects the cooperation on regular ring networks, square lattice, random and scale-free networks, respectively. The results for the square lattice and regular ring networks are demonstrated by the pair approximation.

Adaptive categorization of ART networks in robot behavior learning using game-theoretic formulation.

PubMed

Fung, Wai-keung; Liu, Yun-hui

2003-12-01

Adaptive Resonance Theory (ART) networks are employed in robot behavior learning. Two of the difficulties in online robot behavior learning, namely, (1) exponential memory increases with time, (2) difficulty for operators to specify learning tasks accuracy and control learning attention before learning. In order to remedy the aforementioned difficulties, an adaptive categorization mechanism is introduced in ART networks for perceptual and action patterns categorization in this paper. A game-theoretic formulation of adaptive categorization for ART networks is proposed for vigilance parameter adaptation for category size control on the categories formed. The proposed vigilance parameter update rule can help improving categorization performance in the aspect of category number stability and solve the problem of selecting initial vigilance parameter prior to pattern categorization in traditional ART networks. Behavior learning using physical robot is conducted to demonstrate the effectiveness of the proposed adaptive categorization mechanism in ART networks.

Evolutionary mixed games in structured populations: Cooperation and the benefits of heterogeneity

NASA Astrophysics Data System (ADS)

Amaral, Marco A.; Wardil, Lucas; Perc, Matjaž; da Silva, Jafferson K. L.

2016-04-01

Evolutionary games on networks traditionally involve the same game at each interaction. Here we depart from this assumption by considering mixed games, where the game played at each interaction is drawn uniformly at random from a set of two different games. While in well-mixed populations the random mixture of the two games is always equivalent to the average single game, in structured populations this is not always the case. We show that the outcome is, in fact, strongly dependent on the distance of separation of the two games in the parameter space. Effectively, this distance introduces payoff heterogeneity, and the average game is returned only if the heterogeneity is small. For higher levels of heterogeneity the distance to the average game grows, which often involves the promotion of cooperation. The presented results support preceding research that highlights the favorable role of heterogeneity regardless of its origin, and they also emphasize the importance of the population structure in amplifying facilitators of cooperation.

Evolutionary mixed games in structured populations: Cooperation and the benefits of heterogeneity.

PubMed

Amaral, Marco A; Wardil, Lucas; Perc, Matjaž; da Silva, Jafferson K L

2016-04-01

Evolutionary games on networks traditionally involve the same game at each interaction. Here we depart from this assumption by considering mixed games, where the game played at each interaction is drawn uniformly at random from a set of two different games. While in well-mixed populations the random mixture of the two games is always equivalent to the average single game, in structured populations this is not always the case. We show that the outcome is, in fact, strongly dependent on the distance of separation of the two games in the parameter space. Effectively, this distance introduces payoff heterogeneity, and the average game is returned only if the heterogeneity is small. For higher levels of heterogeneity the distance to the average game grows, which often involves the promotion of cooperation. The presented results support preceding research that highlights the favorable role of heterogeneity regardless of its origin, and they also emphasize the importance of the population structure in amplifying facilitators of cooperation.

Quantum Bayesian networks with application to games displaying Parrondo's paradox

NASA Astrophysics Data System (ADS)

Pejic, Michael

Bayesian networks and their accompanying graphical models are widely used for prediction and analysis across many disciplines. We will reformulate these in terms of linear maps. This reformulation will suggest a natural extension, which we will show is equivalent to standard textbook quantum mechanics. Therefore, this extension will be termed quantum. However, the term quantum should not be taken to imply this extension is necessarily only of utility in situations traditionally thought of as in the domain of quantum mechanics. In principle, it may be employed in any modelling situation, say forecasting the weather or the stock market---it is up to experiment to determine if this extension is useful in practice. Even restricting to the domain of quantum mechanics, with this new formulation the advantages of Bayesian networks can be maintained for models incorporating quantum and mixed classical-quantum behavior. The use of these will be illustrated by various basic examples. Parrondo's paradox refers to the situation where two, multi-round games with a fixed winning criteria, both with probability greater than one-half for one player to win, are combined. Using a possibly biased coin to determine the rule to employ for each round, paradoxically, the previously losing player now wins the combined game with probabilitygreater than one-half. Using the extended Bayesian networks, we will formulate and analyze classical observed, classical hidden, and quantum versions of a game that displays this paradox, finding bounds for the discrepancy from naive expectations for the occurrence of the paradox. A quantum paradox inspired by Parrondo's paradox will also be analyzed. We will prove a bound for the discrepancy from naive expectations for this paradox as well. Games involving quantum walks that achieve this bound will be presented.

Capability and Interface Assessment of Gaming Technologies for Future Multi-Unmanned Air Vehicle Systems

DTIC Science & Technology

2011-08-01

resource management games (e.g., Sim City 2000), board game simulations (e.g., VASSAL), and abstract games (e.g., Tetris). The second purpose of the...which occur simultaneously o E.g., Starcraft  Board game o A computer game that emulates a board game o E.g., Archon  2D Side View o A game...a mouse  Joypad o E.g., A playstation/X-box controller  Accelerometer o E.g., A Wii Controller  Touch 22 Distribution A: Approved for

CyFall: A Cyber-Network Game Scenario

DTIC Science & Technology

2014-08-01

results. This report examines the development of a conceptual game ( gamification ) that would aid nonexperts in identifying with their role and the...user study, gamification 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18. NUMBER OF PAGES 36 19a

The scientific learning approach using multimedia-based maze game to improve learning outcomes

NASA Astrophysics Data System (ADS)

Setiawan, Wawan; Hafitriani, Sarah; Prabawa, Harsa Wara

2016-02-01

The objective of curriculum 2013 is to improve the quality of education in Indonesia, which leads to improving the quality of learning. The scientific approach and supported empowerment media is one approach as massaged of curriculum 2013. This research aims to design a labyrinth game based multimedia and apply in the scientific learning approach. This study was conducted in one of the Vocational School in Subjects of Computer Network on 2 (two) classes of experimental and control. The method used Mix Method Research (MMR) which combines qualitative in multimedia design, and quantitative in the study of learning impact. The results of a survey showed that the general of vocational students like of network topology material (68%), like multimedia (74%), and in particular, like interactive multimedia games and flash (84%). Multimediabased maze game developed good eligibility based on media and material aspects of each value 840% and 82%. Student learning outcomes as a result of using a scientific approach to learning with a multimediabased labyrinth game increase with an average of gain index about (58%) and higher than conventional multimedia with index average gain of 0.41 (41%). Based on these results the scientific approach to learning by using multimediabased labyrinth game can improve the quality of learning and increase understanding of students. Multimedia of learning based labyrinth game, which developed, got a positive response from the students with a good qualification level (75%).

Energy Efficiency in Public Buildings through Context-Aware Social Computing.

PubMed

García, Óscar; Alonso, Ricardo S; Prieto, Javier; Corchado, Juan M

2017-04-11

The challenge of promoting behavioral changes in users that leads to energy savings in public buildings has become a complex task requiring the involvement of multiple technologies. Wireless sensor networks have a great potential for the development of tools, such as serious games, that encourage acquiring good energy and healthy habits among users in the workplace. This paper presents the development of a serious game using CAFCLA, a framework that allows for integrating multiple technologies, which provide both context-awareness and social computing. Game development has shown that the data provided by sensor networks encourage users to reduce energy consumption in their workplace and that social interactions and competitiveness allow for accelerating the achievement of good results and behavioral changes that favor energy savings.

Assortative and dissortative priorities for game interaction and strategy adaptation significantly bolster network reciprocity in the prisoner’s dilemma

NASA Astrophysics Data System (ADS)

Tanimoto, Jun

2014-05-01

In 2 × 2 prisoner’s dilemma games, network reciprocity is one mechanism for adding social viscosity, which leads to cooperative equilibrium. Here we show that combining the process for selecting a gaming partner with the process for selecting an adaptation partner significantly enhances cooperation, even though such selection processes require additional costs to collect further information concerning which neighbor should be chosen. Based on elaborate investigations of the dynamics generated by our model, we find that high levels of cooperation result from two kinds of behavior: cooperators tend to interact with cooperators to prevent being exploited by defectors and defectors tend to choose cooperators to exploit despite the possibility that some defectors convert to cooperators.

Optimal convergence in naming game with geography-based negotiation on small-world networks

NASA Astrophysics Data System (ADS)

Liu, Run-Ran; Wang, Wen-Xu; Lai, Ying-Cheng; Chen, Guanrong; Wang, Bing-Hong

2011-01-01

We propose a negotiation strategy to address the effect of geography on the dynamics of naming games over small-world networks. Communication and negotiation frequencies between two agents are determined by their geographical distance in terms of a parameter characterizing the correlation between interaction strength and the distance. A finding is that there exists an optimal parameter value leading to fastest convergence to global consensus on naming. Numerical computations and a theoretical analysis are provided to substantiate our findings.

Adaptive, Distributed Control of Constrained Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Bieniawski, Stefan; Wolpert, David H.

2004-01-01

Product Distribution (PO) theory was recently developed as a broad framework for analyzing and optimizing distributed systems. Here we demonstrate its use for adaptive distributed control of Multi-Agent Systems (MASS), i.e., for distributed stochastic optimization using MAS s. First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (Probability dist&&on on the joint state of the agents. When the game in question is a team game with constraints, that equilibrium optimizes the expected value of the team game utility, subject to those constraints. One common way to find that equilibrium is to have each agent run a Reinforcement Learning (E) algorithm. PD theory reveals this to be a particular type of search algorithm for minimizing the Lagrangian. Typically that algorithm i s quite inefficient. A more principled alternative is to use a variant of Newton's method to minimize the Lagrangian. Here we compare this alternative to RL-based search in three sets of computer experiments. These are the N Queen s problem and bin-packing problem from the optimization literature, and the Bar problem from the distributed RL literature. Our results confirm that the PD-theory-based approach outperforms the RL-based scheme in all three domains.

Coevolution of Vertex Weights Resolves Social Dilemma in Spatial Networks.

PubMed

Shen, Chen; Chu, Chen; Guo, Hao; Shi, Lei; Duan, Jiangyan

2017-11-09

In realistic social system, the role or influence of each individual varies and adaptively changes in time in the population. Inspired by this fact, we thus consider a new coevolution setup of game strategy and vertex weight on a square lattice. In detail, we model the structured population on a square lattice, on which the role or influence of each individual is depicted by vertex weight, and the prisoner's dilemma game has been applied to describe the social dilemma of pairwise interactions of players. Through numerical simulation, we conclude that our coevolution setup can promote the evolution of cooperation effectively. Especially, there exists a moderate value of δ for each ε that can warrant an optimal resolution of social dilemma. For a further understanding of these results, we find that intermediate value of δ enables the strongest heterogeneous distribution of vertex weight. We hope our coevolution setup of vertex weight will provide new insight for the future research.

A Comparison of Techniques for Camera Selection and Hand-Off in a Video Network

NASA Astrophysics Data System (ADS)

Li, Yiming; Bhanu, Bir

Video networks are becoming increasingly important for solving many real-world problems. Multiple video sensors require collaboration when performing various tasks. One of the most basic tasks is the tracking of objects, which requires mechanisms to select a camera for a certain object and hand-off this object from one camera to another so as to accomplish seamless tracking. In this chapter, we provide a comprehensive comparison of current and emerging camera selection and hand-off techniques. We consider geometry-, statistics-, and game theory-based approaches and provide both theoretical and experimental comparison using centralized and distributed computational models. We provide simulation and experimental results using real data for various scenarios of a large number of cameras and objects for in-depth understanding of strengths and weaknesses of these techniques.

Properties of on-line social systems

NASA Astrophysics Data System (ADS)

Grabowski, A.; Kruszewska, N.; Kosiński, R. A.

2008-11-01

We study properties of five different social systems: (i) internet society of friends consisting of over 106 people, (ii) social network consisting of 3 × 104 individuals, who interact in a large virtual world of Massive Multiplayer Online Role Playing Games (MMORPGs), (iii) over 106 users of music community website, (iv) over 5 × 106 users of gamers community server and (v) over 0.25 × 106 users of books admirer website. Individuals included in large social network form an Internet community and organize themselves in groups of different sizes. The destiny of those systems, as well as the method of creating of new connections, are different, however we found that the properties of these networks are very similar. We have found that the network components size distribution follow the power-law scaling form. In all five systems we have found interesting scaling laws concerning human dynamics. Our research has shown how long people are interested in a single task, how much time they devote to it and how fast they are making friends. It is surprising that the time evolution of an individual connectivity is very similar in each system.

Using posts to an online social network to assess fishing effort

USGS Publications Warehouse

Martin, Dustin R.; Chizinski, Christopher J.; Eskridge, Kent M.; Pope, Kevin L

2014-01-01

Fisheries management has evolved from reservoir to watershed management, creating a need to simultaneously gather information within and across interacting reservoirs. However, costs to gather information on the fishing effort on multiple reservoirs using traditional creel methodology are often prohibitive. Angler posts about reservoirs online provide a unique medium to test hypotheses on the distribution of fishing pressure. We show that the activity on an online fishing social network is related to fishing effort and can be used to facilitate management goals. We searched the Nebraska Fish and Game Association Fishing Forum for all references from April 2009 to December 2010 to 19 reservoirs that comprise the Salt Valley regional fishery in southeastern Nebraska. The number of posts was positively related to monthly fishing effort on a regional scale, with individual reservoirs having the most annual posts also having the most annual fishing effort. Furthermore, this relationship held temporally. Online fishing social networks provide the potential to assess effort on larger spatial scales than currently feasible.

On delay adjustment for dynamic load balancing in distributed virtual environments.

PubMed

Deng, Yunhua; Lau, Rynson W H

2012-04-01

Distributed virtual environments (DVEs) are becoming very popular in recent years, due to the rapid growing of applications, such as massive multiplayer online games (MMOGs). As the number of concurrent users increases, scalability becomes one of the major challenges in designing an interactive DVE system. One solution to address this scalability problem is to adopt a multi-server architecture. While some methods focus on the quality of partitioning the load among the servers, others focus on the efficiency of the partitioning process itself. However, all these methods neglect the effect of network delay among the servers on the accuracy of the load balancing solutions. As we show in this paper, the change in the load of the servers due to network delay would affect the performance of the load balancing algorithm. In this work, we conduct a formal analysis of this problem and discuss two efficient delay adjustment schemes to address the problem. Our experimental results show that our proposed schemes can significantly improve the performance of the load balancing algorithm with neglectable computation overhead.

Weiqi games as a tree: Zipf's law of openings and beyond

NASA Astrophysics Data System (ADS)

Xu, Li-Gong; Li, Ming-Xia; Zhou, Wei-Xing

2015-06-01

Weiqi is one of the most complex board games played by two persons. The placement strategies adopted by Weiqi players are often used to analog the philosophy of human wars. Contrary to the western chess, Weiqi games are less studied by academics partially because Weiqi is popular only in East Asia, especially in China, Japan and Korea. Here, we propose to construct a directed tree using a database of extensive Weiqi games and perform a quantitative analysis of the Weiqi tree. We find that the popularity distribution of Weiqi openings with the same number of moves is distributed according to a power law and the tail exponent increases with the number of moves. Intriguingly, the superposition of the popularity distributions of Weiqi openings with a number of moves not higher than a given number also has a power-law tail in which the tail exponent increases with the number of moves, and the superposed distribution approaches the Zipf law. These findings are the same as for chess and support the conjecture that the popularity distribution of board game openings follows the Zipf law with a universal exponent. We also find that the distribution of out-degrees has a power-law form, the distribution of branching ratios has a very complicated pattern, and the distribution of uniqueness scores defined by the path lengths from the root vertex to the leaf vertices exhibits a unimodal shape. Our work provides a promising direction for the study of the decision-making process of Weiqi playing from the perspective of directed branching tree.

The evolution of altruism in spatial threshold public goods games via an insurance mechanism

NASA Astrophysics Data System (ADS)

Zhang, Jianlei; Zhang, Chunyan

2015-05-01

The persistence of cooperation in public goods situations has become an important puzzle for researchers. This paper considers the threshold public goods games where the option of insurance is provided for players from the standpoint of diversification of risk, envisaging the possibility of multiple strategies in such scenarios. In this setting, the provision point is defined in terms of the minimum number of contributors in one threshold public goods game, below which the game fails. In the presence of risk and insurance, more contributions are motivated if (1) only cooperators can opt to be insured and thus their contribution loss in the aborted games can be (partly or full) covered by the insurance; (2) insured cooperators obtain larger compensation, at lower values of the threshold point (the required minimum number of contributors). Moreover, results suggest the dominance of insured defectors who get a better promotion by more profitable benefits from insurance. We provide results of extensive computer simulations in the realm of spatial games (random regular networks and scale-free networks here), and support this study with analytical results for well-mixed populations. Our study is expected to establish a causal link between the widespread altruistic behaviors and the existing insurance system.

Cooperative Game-Based Energy Efficiency Management over Ultra-Dense Wireless Cellular Networks

PubMed Central

Li, Ming; Chen, Pengpeng; Gao, Shouwan

2016-01-01

Ultra-dense wireless cellular networks have been envisioned as a promising technique for handling the explosive increase of wireless traffic volume. With the extensive deployment of small cells in wireless cellular networks, the network spectral efficiency (SE) is improved with the use of limited frequency. However, the mutual inter-tier and intra-tier interference between or among small cells and macro cells becomes serious. On the other hand, more chances for potential cooperation among different cells are introduced. Energy efficiency (EE) has become one of the most important problems for future wireless networks. This paper proposes a cooperative bargaining game-based method for comprehensive EE management in an ultra-dense wireless cellular network, which highlights the complicated interference influence on energy-saving challenges and the power-coordination process among small cells and macro cells. Especially, a unified EE utility with the consideration of the interference mitigation is proposed to jointly address the SE, the deployment efficiency (DE), and the EE. In particular, closed-form power-coordination solutions for the optimal EE are derived to show the convergence property of the algorithm. Moreover, a simplified algorithm is presented to reduce the complexity of the signaling overhead, which is significant for ultra-dense small cells. Finally, numerical simulations are provided to illustrate the efficiency of the proposed cooperative bargaining game-based and simplified schemes. PMID:27649170

Cooperative Game-Based Energy Efficiency Management over Ultra-Dense Wireless Cellular Networks.

PubMed

Li, Ming; Chen, Pengpeng; Gao, Shouwan

2016-09-13

Ultra-dense wireless cellular networks have been envisioned as a promising technique for handling the explosive increase of wireless traffic volume. With the extensive deployment of small cells in wireless cellular networks, the network spectral efficiency (SE) is improved with the use of limited frequency. However, the mutual inter-tier and intra-tier interference between or among small cells and macro cells becomes serious. On the other hand, more chances for potential cooperation among different cells are introduced. Energy efficiency (EE) has become one of the most important problems for future wireless networks. This paper proposes a cooperative bargaining game-based method for comprehensive EE management in an ultra-dense wireless cellular network, which highlights the complicated interference influence on energy-saving challenges and the power-coordination process among small cells and macro cells. Especially, a unified EE utility with the consideration of the interference mitigation is proposed to jointly address the SE, the deployment efficiency (DE), and the EE. In particular, closed-form power-coordination solutions for the optimal EE are derived to show the convergence property of the algorithm. Moreover, a simplified algorithm is presented to reduce the complexity of the signaling overhead, which is significant for ultra-dense small cells. Finally, numerical simulations are provided to illustrate the efficiency of the proposed cooperative bargaining game-based and simplified schemes.

Business game using information technologies for the students of final courses to direction of telecommunication

NASA Astrophysics Data System (ADS)

Khmelevskaya, A. V.; Klyuchnikova, O. E.; Golovin, P. V.; Yakushev, A. S.

2017-01-01

This article discusses the use of business games in the field of Infocommunications and information security. The authors consider the developed business game "Interview - rules of successful employment," "The tender to design Local Area Network," "Emergency situation in telecommunications company." This business games allows students to develop many skills and abilities. This games gives students the opportunity to take advantage of their theoretical knowledge and already in student years to begin them practically to realize and apply, producing own preparation the same for a further successful professional growth. The games is recommended for use as a new integrated form of organization-semester independent students work with a public defense of result and demonstration all professional competencies.

Comparing the Effects of Bupropion and Escitalopram on Excessive Internet Game Play in Patients with Major Depressive Disorder.

PubMed

Nam, Beomwoo; Bae, Sujin; Kim, Sun Mi; Hong, Ji Seon; Han, Doug Hyun

2017-11-30

Several studies have suggested the efficacy of bupropion and escitalopram on reducing the excessive internet game play. We hypothesized that both bupropion and escitalopram would be effective on reducing the severity of depressive symptoms and internet gaming disorder (IGD) symptoms in patients with both major depressive disorder and IGD. However, the changes in brain connectivity between the default mode network (DMN) and the salience network were different between bupropion and escitalopram due to their different pharmacodynamics. This study was designed as a 12-week double blind prospective trial. Thirty patients were recruited for this research (15 bupropion group+15 escitalopram group). To assess the differential functional connectivity (FC) between the hubs of the DMN and the salience network, we selected 12 regions from the automated anatomical labeling in PickAtals software. After drug treatment, the depressive symptoms and IGD symptoms in both groups were improved. Impulsivity and attentional symptoms in the bupropion group were significantly decreased, compared to the escitalopram group. After treatment, FC within only the DMN in escitalopram decreased while FC between DMN and salience network in bupropion group decreased. Bupropion was associated with significantly decreased FC within the salience network and between the salience network and the DMN, compared to escitalopram. Bupropion showed greater effects than escitalopram on reducing impulsivity and attentional symptoms. Decreased brain connectivity between the salience network and the DMN appears to be associated with improved excessive IGD symptoms and impulsivity in MDD patients with IGD.

Distributed Observer Network

NASA Technical Reports Server (NTRS)

Conroy, Michael; Mazzone, Rebecca; Little, William; Elfrey, Priscilla; Mann, David; Mabie, Kevin; Cuddy, Thomas; Loundermon, Mario; Spiker, Stephen; McArthur, Frank;

Complex network study of Brazilian soccer players

NASA Astrophysics Data System (ADS)

Onody, Roberto N.; de Castro, Paulo A.

2004-09-01

Although being a very popular sport in many countries, soccer has not received much attention from the scientific community. In this paper, we study soccer from a complex network point of view. First, we consider a bipartite network with two kinds of vertices or nodes: the soccer players and the clubs. Real data were gathered from the 32 editions of the Brazilian soccer championship, in a total of 13411 soccer players and 127 clubs. We find a lot of interesting and perhaps unsuspected results. The probability that a Brazilian soccer player has worked at N clubs or played M games shows an exponential decay while the probability that he has scored G goals is power law. Now, if two soccer players who have worked at the same club at the same time are connected by an edge, then a new type of network arises (composed exclusively by soccer player nodes). Our analysis shows that for this network the degree distribution decays exponentially. We determine the exact values of the clustering coefficient, the assortativity coefficient and the average shortest path length and compare them with those of the Erdös-Rényi and configuration model. The time evolution of these quantities are calculated and the corresponding results discussed.

List of U.S. Army Research Institute Research and Technical Publications for Public Release/Unlimited Distribution, Fiscal Year 2008

DTIC Science & Technology

2009-11-01

times were shorter, collisions were fewer, and more targets were photographed. Effects of video game experience and spatial ability were also...Control Spatial ability, video game , user-interface, remote control, robot TR 1230 The Perception and Estimation of Egocentric Distance in Real and...development by RDECOM-STTC, and ARI is using the AW-VTT to research challenges in the use of distributed, game -based simulations for training

Brain Training with Video Games in Covert Hepatic Encephalopathy.

PubMed

Bajaj, Jasmohan S; Ahluwalia, Vishwadeep; Thacker, Leroy R; Fagan, Andrew; Gavis, Edith A; Lennon, Michael; Heuman, Douglas M; Fuchs, Michael; Wade, James B

2017-02-01

Despite the associated adverse outcomes, pharmacologic intervention for covert hepatic encephalopathy (CHE) is not the standard of care. We hypothesized that a video game-based rehabilitation program would improve white matter integrity and brain connectivity in the visuospatial network on brain magnetic resonance imaging (MRI), resulting in improved cognitive function in CHE subjects on measures consistent with the cognitive skill set emphasized by the two video games (e.g., IQ Boost-visual working memory, and Aim and Fire Challenge-psychomotor speed), but also generalize to thinking skills beyond the focus of the cognitive training (Hopkins verbal learning test (HVLT)-verbal learning/memory) and improve their health-related quality of life (HRQOL). The trial included three phases over 8 weeks; during the learning phase (cognitive tests administered twice over 2 weeks without intervening intervention), training phase (daily video game training for 4 weeks), and post-training phase (testing 2 weeks after the video game training ended). Thirty CHE patients completed all visits with significant daily achievement on the video games. In a subset of 13 subjects that underwent brain MRI, there was a significant decrease in fractional anisotropy, and increased radial diffusivity (suggesting axonal sprouting or increased cross-fiber formation) involving similar brain regions (i.e., corpus callosum, internal capsule, and sections of the corticospinal tract) and improvement in the visuospatial resting-state connectivity corresponding to the video game training domains. No significant corresponding improvement in HRQOL or HVLT performance was noted, but cognitive performance did transiently improve on cognitive tests similar to the video games during training. Although multimodal brain imaging changes suggest reductions in tract edema and improved neural network connectivity, this trial of video game brain training did not improve the HRQOL or produce lasting improvement in cognitive function in patients with CHE.

Decreased functional connectivity of insula-based network in young adults with internet gaming disorder.

PubMed

Zhang, Yanzhen; Mei, Wei; Zhang, John X; Wu, Qiulin; Zhang, Wei

2016-09-01

The insula is a region that integrates interoception and drug urges, but little is known about its role in behavioral addiction such as internet addiction. We investigated insula-based functional connectivity in participants with internet gaming disorder (IGD) and healthy controls (HC) using resting-state functional MRI. The right and left insula subregions (posterior, ventroanterior, and dorsoanterior) were used as seed regions in a connectivity analysis. Compared with the HC group, the IGD group showed decreased functional connectivity between left posterior insula and bilateral supplementary motor area and middle cingulated cortex, between right posterior insula and right superior frontal gyrus, and decreased functional integration between insular subregions. The finding of reduced functional connectivity between the interoception and the motor/executive control regions is interpreted to reflect reduced ability to inhibit motor responses to internet gaming or diminished executive control over craving for internet gaming in IGD. The results support the hypothesis that IGD is associated with altered insula-based network, similar to substance addiction such as smoking.

Cournot games with network effects for electric power markets

NASA Astrophysics Data System (ADS)

Spezia, Carl John

The electric utility industry is moving from regulated monopolies with protected service areas to an open market with many wholesale suppliers competing for consumer load. This market is typically modeled by a Cournot game oligopoly where suppliers compete by selecting profit maximizing quantities. The classical Cournot model can produce multiple solutions when the problem includes typical power system constraints. This work presents a mathematical programming formulation of oligopoly that produces unique solutions when constraints limit the supplier outputs. The formulation casts the game as a supply maximization problem with power system physical limits and supplier incremental profit functions as constraints. The formulation gives Cournot solutions identical to other commonly used algorithms when suppliers operate within the constraints. Numerical examples demonstrate the feasibility of the theory. The results show that the maximization formulation will give system operators more transmission capacity when compared to the actions of suppliers in a classical constrained Cournot game. The results also show that the profitability of suppliers in constrained networks depends on their location relative to the consumers' load concentration.

A Virtual Hosting Environment for Distributed Online Gaming

NASA Astrophysics Data System (ADS)

Brossard, David; Prieto Martinez, Juan Luis

With enterprise boundaries becoming fuzzier, it’s become clear that businesses need to share resources, expose services, and interact in many different ways. In order to achieve such a distribution in a dynamic, flexible, and secure way, we have designed and implemented a virtual hosting environment (VHE) which aims at integrating business services across enterprise boundaries and virtualising the ICT environment within which these services operate in order to exploit economies of scale for the businesses as well as achieve shorter concept-to-market time scales. To illustrate the relevance of the VHE, we have applied it to the online gaming world. Online gaming is an early adopter of distributed computing and more than 30% of gaming developer companies, being aware of the shift, are focusing on developing high performance platforms for the new online trend.

Violence in television commercials during nonviolent programming. The 1996 Major League Baseball playoffs.

PubMed

Anderson, C

1997-10-01

To identify the frequency of violent television commercials aired during major league baseball playoffs, traditionally thought to be a family-oriented viewing time. All 6 World Series games televised on the Fox Television Network (Fox), all 5 American League Championship Series playoff games televised by the National Broadcasting Company (NBC), and 4 first-round playoff games televised by ESPN Sports Television Network (ESPN) were videotaped in October 1996. During the 15 televised games reviewed, 104 (6.8%) of the 1528 commercials contained violent content. Sixty-one commercials (10 per game) that included violent interactions were noted during the World Series, 30 (6 per game) during the American League Championship Series, and 13 (3 per game) during the 4 first-round playoff games for a total of 104. In these 104 violent commercials, 69 contained at least 1 violent act, 90 contained at least 1 violent threat, and 27 contained evidence of at least 1 violent consequence. Seventy (67.3%) of the violent commercials were promotions for television programs, 7 (6.7%) were cable television program advertisements, and 20 (19.2%) were big-screen movie promotions. Twenty (71.4%) of 28 big-screen movie promotions were violent. Twenty-two (21.2%) of the 104 violent commercials and 7 "nonviolent" commercials contained blood or other graphic content, all of which were televised during the Fox presentation of the World Series. Fox also accounted for all 24 violent commercials that used a knife. Guns were involved in 25 violent commercials on NBC (5.0 per game), in 20 on Fox (3.33 per game), and in 7 on ESPN (1.75 per game). Overt violent content in commercials during the 1996 major league playoffs was common and consisted mainly of promotions for television programs and big-screen movies. It is counterintuitive to find such commercials in nonviolent programming and makes it difficult for parents to avoid exposing their children to this form of violence.

A 3D Active Learning Application for NeMO-Net, the NASA Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

NASA Technical Reports Server (NTRS)

van den Bergh, Jarrett; Schutz, Joey; Li, Alan; Chirayath, Ved

2017-01-01

NeMO-Net, the NASA neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive video game prototype for tablet and mobile devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using fluid lensing to create a dataset that will be used to train NeMO-Nets convolutional neural network. The application currently allows for users to classify preselected regions of coral in the Pacific and will be expanded to include additional regions captured using our NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as lower-resolution airborne remote sensing data from the ongoing NASA CORAL campaign. Active learning applications present a novel methodology for efficiently training large-scale Neural Networks wherein variances in identification can be rapidly mitigated against control data. NeMO-Net periodically checks users input against pre-classified coral imagery to gauge their accuracy and utilize in-game mechanics to provide classification training. Users actively communicate with a server and are requested to classify areas of coral for which other users had conflicting classifications and contribute their input to a larger database for ranking. In partnering with Mission Blue and IUCN, NeMO-Net leverages an international consortium of subject matter experts to classify areas of confusion identified by NeMO-Net and generate additional labels crucial for identifying decision boundary locations in coral reef assessment.

A 3D Active Learning Application for NeMO-Net, the NASA Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

NASA Astrophysics Data System (ADS)

van den Bergh, J.; Schutz, J.; Chirayath, V.; Li, A.

2017-12-01

NeMO-Net, the NASA neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive video game prototype for tablet and mobile devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using fluid lensing to create a dataset that will be used to train NeMO-Net's convolutional neural network. The application currently allows for users to classify preselected regions of coral in the Pacific and will be expanded to include additional regions captured using our NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as lower-resolution airborne remote sensing data from the ongoing NASA CORAL campaign.Active learning applications present a novel methodology for efficiently training large-scale Neural Networks wherein variances in identification can be rapidly mitigated against control data. NeMO-Net periodically checks users' input against pre-classified coral imagery to gauge their accuracy and utilizes in-game mechanics to provide classification training. Users actively communicate with a server and are requested to classify areas of coral for which other users had conflicting classifications and contribute their input to a larger database for ranking. In partnering with Mission Blue and IUCN, NeMO-Net leverages an international consortium of subject matter experts to classify areas of confusion identified by NeMO-Net and generate additional labels crucial for identifying decision boundary locations in coral reef assessment.

Impaired anterior insular activation during risky decision making in young adults with internet gaming disorder.

PubMed

Lee, Deokjong; Lee, Junghan; Yoon, Kang Joon; Kee, Namkoong; Jung, Young-Chul

2016-05-25

Internet gaming disorder is defined as excessive and compulsive use of the internet to engage in games that leads to clinically significant psychosocial impairment. We tested the hypothesis that individuals with internet gaming disorder would be less sensitive to high-risk situations and show aberrant brain activation related to risk prediction processing. Young adults with internet gaming disorder underwent functional MRI while performing a risky decision-making task. The healthy control group showed stronger activations within the dorsal attention network and the anterior insular cortex, which were not found in the internet gaming disorder group. Our findings imply that young adults with internet gaming disorder show impaired anterior insular activation during risky decision making, which might make them vulnerable when they need to adapt new behavioral strategies in high-risk situations.

Lognormal Behavior of the Size Distributions of Animation Characters

NASA Astrophysics Data System (ADS)

Yamamoto, Ken

This study investigates the statistical property of the character sizes of animation, superhero series, and video game. By using online databases of Pokémon (video game) and Power Rangers (superhero series), the height and weight distributions are constructed, and we find that the weight distributions of Pokémon and Zords (robots in Power Rangers) follow the lognormal distribution in common. For the theoretical mechanism of this lognormal behavior, the combination of the normal distribution and the Weber-Fechner law is proposed.

Preferential selection based on degree difference in the spatial prisoner's dilemma games

NASA Astrophysics Data System (ADS)

Huang, Changwei; Dai, Qionglin; Cheng, Hongyan; Li, Haihong

2017-10-01

Strategy evolution in spatial evolutionary games is generally implemented through imitation processes between individuals. In most previous studies, it is assumed that individuals pick up one of their neighbors randomly to learn from. However, by considering the heterogeneity of individuals' influence in the real society, preferential selection is more realistic. Here, we introduce a preferential selection mechanism based on degree difference into spatial prisoner's dilemma games on Erdös-Rényi networks and Barabási-Albert scale-free networks and investigate the effects of the preferential selection on cooperation. The results show that, when the individuals prefer to choose the neighbors who have small degree difference with themselves to imitate, cooperation is hurt by the preferential selection. In contrast, when the individuals prefer to choose those large degree difference neighbors to learn from, there exists optimal preference strength resulting in the maximal cooperation level no matter what the network structure is. In addition, we investigate the robustness of the results against variations of the noise, the average degree and the size of network in the model, and find that the qualitative features of the results are unchanged.

Best response game of traffic on road network of non-signalized intersections

NASA Astrophysics Data System (ADS)

Yao, Wang; Jia, Ning; Zhong, Shiquan; Li, Liying

2018-01-01

This paper studies the traffic flow in a grid road network with non-signalized intersections. The nature of the drivers in the network is simulated such that they play an iterative snowdrift game with other drivers. A cellular automata model is applied to study the characteristics of the traffic flow and the evolution of the behaviour of the drivers during the game. The drivers use best-response as their strategy to update rules. Three major findings are revealed. First, the cooperation rate in simulation experiences staircase-shaped drop as cost to benefit ratio r increases, and cooperation rate can be derived analytically as a function of cost to benefit ratio r. Second, we find that higher cooperation rate corresponds to higher average speed, lower density and higher flow. This reveals that defectors deteriorate the efficiency of traffic on non-signalized intersections. Third, the system experiences more randomness when the density is low because the drivers will not have much opportunity to update strategy when the density is low. These findings help to show how the strategy of drivers in a traffic network evolves and how their interactions influence the overall performance of the traffic system.

Dysfunctional default mode network and executive control network in people with Internet gaming disorder: Independent component analysis under a probability discounting task.

PubMed

Wang, L; Wu, L; Lin, X; Zhang, Y; Zhou, H; Du, X; Dong, G

2016-04-01

The present study identified the neural mechanism of risky decision-making in Internet gaming disorder (IGD) under a probability discounting task. Independent component analysis was used on the functional magnetic resonance imaging data from 19 IGD subjects (22.2 ± 3.08 years) and 21 healthy controls (HC, 22.8 ± 3.5 years). For the behavioral results, IGD subjects prefer the risky to the fixed options and showed shorter reaction time compared to HC. For the imaging results, the IGD subjects showed higher task-related activity in default mode network (DMN) and less engagement in the executive control network (ECN) than HC when making the risky decisions. Also, we found the activities of DMN correlate negatively with the reaction time and the ECN correlate positively with the probability discounting rates. The results suggest that people with IGD show altered modulation in DMN and deficit in executive control function, which might be the reason for why the IGD subjects continue to play online games despite the potential negative consequences. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Energy Efficiency in Public Buildings through Context-Aware Social Computing

PubMed Central

García, Óscar; Alonso, Ricardo S.; Prieto, Javier; Corchado, Juan M.

2017-01-01

The challenge of promoting behavioral changes in users that leads to energy savings in public buildings has become a complex task requiring the involvement of multiple technologies. Wireless sensor networks have a great potential for the development of tools, such as serious games, that encourage acquiring good energy and healthy habits among users in the workplace. This paper presents the development of a serious game using CAFCLA, a framework that allows for integrating multiple technologies, which provide both context-awareness and social computing. Game development has shown that the data provided by sensor networks encourage users to reduce energy consumption in their workplace and that social interactions and competitiveness allow for accelerating the achievement of good results and behavioral changes that favor energy savings. PMID:28398237

Imitation versus payoff: Duality of the decision-making process demonstrates criticality and consensus formation

NASA Astrophysics Data System (ADS)

Turalska, M.; West, B. J.

2014-11-01

We consider a dual model of decision making, in which an individual forms its opinion based on contrasting mechanisms of imitation and rational calculation. The decision-making model (DMM) implements imitating behavior by means of a network of coupled two-state master equations that undergoes a phase transition at a critical value of a control parameter. The evolutionary spatial game, being a generalization of the prisoner's dilemma game, is used to determine in objective fashion the cooperative or anticooperative strategy adopted by individuals. Interactions between two sources of dynamics increases the domain of initial states attracted to phase transition dynamics beyond that of the DMM network in isolation. Additionally, on average the influence of the DMM on the game increases the final observed fraction of cooperators in the system.

Prediction of activity type in preschool children using machine learning techniques.

PubMed

Hagenbuchner, Markus; Cliff, Dylan P; Trost, Stewart G; Van Tuc, Nguyen; Peoples, Gregory E

2015-07-01

Recent research has shown that machine learning techniques can accurately predict activity classes from accelerometer data in adolescents and adults. The purpose of this study is to develop and test machine learning models for predicting activity type in preschool-aged children. Participants completed 12 standardised activity trials (TV, reading, tablet game, quiet play, art, treasure hunt, cleaning up, active game, obstacle course, bicycle riding) over two laboratory visits. Eleven children aged 3-6 years (mean age=4.8±0.87; 55% girls) completed the activity trials while wearing an ActiGraph GT3X+ accelerometer on the right hip. Activities were categorised into five activity classes: sedentary activities, light activities, moderate to vigorous activities, walking, and running. A standard feed-forward Artificial Neural Network and a Deep Learning Ensemble Network were trained on features in the accelerometer data used in previous investigations (10th, 25th, 50th, 75th and 90th percentiles and the lag-one autocorrelation). Overall recognition accuracy for the standard feed forward Artificial Neural Network was 69.7%. Recognition accuracy for sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running was 82%, 79%, 64%, 36% and 46%, respectively. In comparison, overall recognition accuracy for the Deep Learning Ensemble Network was 82.6%. For sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running recognition accuracy was 84%, 91%, 79%, 73% and 73%, respectively. Ensemble machine learning approaches such as Deep Learning Ensemble Network can accurately predict activity type from accelerometer data in preschool children. Copyright © 2014 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

The Handicap Principle for Trust in Computer Security, the Semantic Web and Social Networking

NASA Astrophysics Data System (ADS)

Ma, Zhanshan (Sam); Krings, Axel W.; Hung, Chih-Cheng

Communication is a fundamental function of life, and it exists in almost all living things: from single-cell bacteria to human beings. Communication, together with competition and cooperation,arethree fundamental processes in nature. Computer scientists are familiar with the study of competition or 'struggle for life' through Darwin's evolutionary theory, or even evolutionary computing. They may be equally familiar with the study of cooperation or altruism through the Prisoner's Dilemma (PD) game. However, they are likely to be less familiar with the theory of animal communication. The objective of this article is three-fold: (i) To suggest that the study of animal communication, especially the honesty (reliability) of animal communication, in which some significant advances in behavioral biology have been achieved in the last three decades, should be on the verge to spawn important cross-disciplinary research similar to that generated by the study of cooperation with the PD game. One of the far-reaching advances in the field is marked by the publication of "The Handicap Principle: a Missing Piece of Darwin's Puzzle" by Zahavi (1997). The 'Handicap' principle [34][35], which states that communication signals must be costly in some proper way to be reliable (honest), is best elucidated with evolutionary games, e.g., Sir Philip Sidney (SPS) game [23]. Accordingly, we suggest that the Handicap principle may serve as a fundamental paradigm for trust research in computer science. (ii) To suggest to computer scientists that their expertise in modeling computer networks may help behavioral biologists in their study of the reliability of animal communication networks. This is largely due to the historical reason that, until the last decade, animal communication was studied with the dyadic paradigm (sender-receiver) rather than with the network paradigm. (iii) To pose several open questions, the answers to which may bear some refreshing insights to trust research in computer science, especially secure and resilient computing, the semantic web, and social networking. One important thread unifying the three aspects is the evolutionary game theory modeling or its extensions with survival analysis and agreement algorithms [19][20], which offer powerful game models for describing time-, space-, and covariate-dependent frailty (uncertainty and vulnerability) and deception (honesty).

Recommendations for Model Driven Paradigms for Integrated Approaches to Cyber Defense

DTIC Science & Technology

2017-03-06

analogy (e.g., Susceptible, Infected, Recovered [SIR]) • Abstract wargaming: game -theoretic model of cyber conflict without modeling the underlying...malware. 3.7 Abstract Wargaming Here, a game -theoretic process is modeled with moves and effects inspired by cyber conflict but without modeling the...underlying processes of cyber attack and defense. Examples in literature include the following: • Cho J-H, Gao J. Cyber war game in temporal networks

Adaptation and survivors in a random Boolean network.

PubMed

Nakamura, Ikuo

2002-04-01

We introduce the competitive agent with imitation strategy in a random Boolean network, in which the agent plays a competitive game that rewards those in minority. After a long time interval, the worst performer changes its strategy to the one of the best and the process is repeated. The network, initially in a chaotic state, evolves to an intermittent state and finally reaches a frozen state. Time series of survived species (whose strategies are imitated by other agents) in the system depend on the connectivity of each agent. In a system with various connectivity groups, the low connectivity groups win the minority game over the high connectivity groups. We also compared the result with mutation strategy system.

The Relationship Between Online Video Game Involvement and Gaming-Related Friendships Among Emotionally Sensitive Individuals

PubMed Central

Domahidi, Emese; Quandt, Thorsten

2014-01-01

Abstract Some researchers believe that online gaming spaces can be socially accommodating environments for socially inhibited individuals, such as the socially inept, socially anxious, or shy. While previous research has examined, and found, significant links between these populations and online video game play, it remains unknown to what extent these spaces are contributing to tangible social benefits for the socially inhibited. The current study addresses this question by evaluating the link between gaming-related friendships and shyness, as quantified by emotional sensitivity. Drawing from a representative sample of German game players, the results indicate that emotionally sensitive players are using online gaming spaces differently from their less emotionally sensitive counterparts and reporting tangible differences in their in-game friendship networks. This suggests that online games hold the potential to be socially advantageous for shy individuals by allowing them to overcome their traditional social difficulties and generate new friendships as well as strengthen old ones. PMID:24660878

The relationship between online video game involvement and gaming-related friendships among emotionally sensitive individuals.

PubMed

Kowert, Rachel; Domahidi, Emese; Quandt, Thorsten

2014-07-01

Some researchers believe that online gaming spaces can be socially accommodating environments for socially inhibited individuals, such as the socially inept, socially anxious, or shy. While previous research has examined, and found, significant links between these populations and online video game play, it remains unknown to what extent these spaces are contributing to tangible social benefits for the socially inhibited. The current study addresses this question by evaluating the link between gaming-related friendships and shyness, as quantified by emotional sensitivity. Drawing from a representative sample of German game players, the results indicate that emotionally sensitive players are using online gaming spaces differently from their less emotionally sensitive counterparts and reporting tangible differences in their in-game friendship networks. This suggests that online games hold the potential to be socially advantageous for shy individuals by allowing them to overcome their traditional social difficulties and generate new friendships as well as strengthen old ones.

What Would a State of the Art Instructional Video Game Look like?

ERIC Educational Resources Information Center

Gee, J. P.

2005-01-01

A good instructional game, like many good commercial games, should be built around what the author calls "authentic professionalism." In such games, skills, knowledge, and values are distributed between the virtual characters and the real-world player in a way that allows the player to experience first-hand how members of that profession think,…

The influence of action video game playing on eye movement behaviour during visual search in abstract, in-game and natural scenes.

PubMed

Azizi, Elham; Abel, Larry A; Stainer, Matthew J

2017-02-01

Action game playing has been associated with several improvements in visual attention tasks. However, it is not clear how such changes might influence the way we overtly select information from our visual world (i.e. eye movements). We examined whether action-video-game training changed eye movement behaviour in a series of visual search tasks including conjunctive search (relatively abstracted from natural behaviour), game-related search, and more naturalistic scene search. Forty nongamers were trained in either an action first-person shooter game or a card game (control) for 10 hours. As a further control, we recorded eye movements of 20 experienced action gamers on the same tasks. The results did not show any change in duration of fixations or saccade amplitude either from before to after the training or between all nongamers (pretraining) and experienced action gamers. However, we observed a change in search strategy, reflected by a reduction in the vertical distribution of fixations for the game-related search task in the action-game-trained group. This might suggest learning the likely distribution of targets. In other words, game training only skilled participants to search game images for targets important to the game, with no indication of transfer to the more natural scene search. Taken together, these results suggest no modification in overt allocation of attention. Either the skills that can be trained with action gaming are not powerful enough to influence information selection through eye movements, or action-game-learned skills are not used when deciding where to move the eyes.

Genetic Associations and Mechanisms in Oncology (GAME-ON): A Network of Consortia for Post-Genome Wide Association (Post-GWA) Research

Cancer.gov

The Genetic Associations and Mechanisms in Oncology's (GAME-ON) overall goal is to foster an intra-disciplinary and collaborative approach to the translation of promising research leads deriving from the initial wave of cancer GWAS.

The Defender's Role in Cyber Security

DOE Office of Scientific and Technical Information (OSTI.GOV)

The embodiment of this work is a table top game to explore cyber security and network defense concepts and cost. The game structure is such that it provides players an immersive environment to play a given role in cyber security to investigate the result of infrastructure and response decisions.

The Electronic Game Gambit.

ERIC Educational Resources Information Center

Bing, Jon

1982-01-01

The rapid evolution of today's video games now fills arcades, snack bars, and homes with an array of highly interactive, graphically vivid technical devices. This electronic environment is creating a worldwide communication network. Developments in this area will be beneficial provided that appropriate media policies can be framed. (Author/JN)

Neural Extensions to Robust Parameter Design

DTIC Science & Technology

2010-09-01

different ANNs to classify a winner in an NBA basketball game based simply on box score data. The results obtained from these authors showed remarkable......27-29, 2009. Loeffelholz, B.J., Bednar, E., & Bauer, K.W. (2009). “Predicting NBA games using neural networks,” Journal of Quantitative Analysis

Air quality in Beijing during the 2008 Olympic Games observed by satellites and ground monitors

NASA Astrophysics Data System (ADS)

Zhao, Q.; Liu, Y.; He, K.; Chen, L.; Wang, Z.; Koutrakis, P.; Christiani, D.

2008-12-01

Beijing's severe air pollution has been a major concern for hosting the 29th Olympic Games and Special Olympic Games from August 8 to August 24, 2008. It was generally expected that its air quality in 2008, at least around the period of Olympic Games, would be significantly improved through aggressive government control measures However, it is also expected that the improvement of air quality will not be sustainable due to high economic costs. Thus, the massive temporary improvement of air quality in Beijing metropolitan area induced by direct government intervention will serve as an extremely rare "natural experiment", generating a great contrast in air pollution levels in a short period of time. A ground measurement campaign was conducted to evaluate the variation of airborne particulate matters (PM2.5 and PM10) levels in Beijing from late July to early September of 2008. Satellite aerosol remote sensing data from MISR, MODIS, and OMI during this period were also analyzed to evaluate the spatial distribution of particles in Beijing and surrounding areas. Preliminary analysis indicated that city-wide ground PM10 level in August was 30% lower than that in 2007. During the Olympic Games, PM10 level was nearly 50% lower than the same period in 2007. There are a total of 14 days with daily PM10 concentrations below 50 micrograms per cubic meter, longest since the ground monitoring network was established in 2001. PM2.5 concentrations measured from three research sites showed a similar reduction. Satellite remote sensing data are limited during the Games due to extensive cloud cover. However, existing data in August and September show a substantial regional reduction of aerosol optical depth. In conclusion, the pollution control measures effectively improved the air quality in Beijing and provided insight on how the Chinese government may mitigate air pollution in many of its large cities.

Inferring Structure and Forecasting Dynamics on Evolving Networks

DTIC Science & Technology

2016-01-05

Graphs ........................................................................................................................ 23 7. Sacred Values...5) Team Formation; (6) Games of Graphs; (7) Sacred Values and Legitimacy in Network Interactions; (8) Network processes in Geo-Social Context. 1...Authority, Cooperation and Competition in Religious Networks Key Papers: McBride 2015a [72] and McBride 2015b [73] McBride (2015a) examines

Is poker a game of skill or chance? A quasi-experimental study.

PubMed

Meyer, Gerhard; von Meduna, Marc; Brosowski, Tim; Hayer, Tobias

2013-09-01

Due to intensive marketing and the rapid growth of online gambling, poker currently enjoys great popularity among large sections of the population. Although poker is legally a game of chance in most countries, some (particularly operators of private poker web sites) argue that it should be regarded as a game of skill or sport because the outcome of the game primarily depends on individual aptitude and skill. The available findings indicate that skill plays a meaningful role; however, serious methodological weaknesses and the absence of reliable information regarding the relative importance of chance and skill considerably limit the validity of extant research. Adopting a quasi-experimental approach, the present study examined the extent to which the influence of poker playing skill was more important than card distribution. Three average players and three experts sat down at a six-player table and played 60 computer-based hands of the poker variant "Texas Hold'em" for money. In each hand, one of the average players and one expert received (a) better-than-average cards (winner's box), (b) average cards (neutral box) and (c) worse-than-average cards (loser's box). The standardized manipulation of the card distribution controlled the factor of chance to determine differences in performance between the average and expert groups. Overall, 150 individuals participated in a "fixed-limit" game variant, and 150 individuals participated in a "no-limit" game variant. ANOVA results showed that experts did not outperform average players in terms of final cash balance. Rather, card distribution was the decisive factor for successful poker playing. However, expert players were better able to minimize losses when confronted with disadvantageous conditions (i.e., worse-than-average cards). No significant differences were observed between the game variants. Furthermore, supplementary analyses confirm differential game-related actions dependent on the card distribution, player status, and game variant. In conclusion, the study findings indicate that poker should be regarded as a game of chance, at least under certain basic conditions, and suggest new directions for further research.

Dependency Links Can Hinder the Evolution of Cooperation in the Prisoner’s Dilemma Game on Lattices and Networks

PubMed Central

Wang, Xuwen; Nie, Sen; Wang, Binghong

2015-01-01

Networks with dependency links are more vulnerable when facing the attacks. Recent research also has demonstrated that the interdependent groups support the spreading of cooperation. We study the prisoner’s dilemma games on spatial networks with dependency links, in which a fraction of individual pairs is selected to depend on each other. The dependency individuals can gain an extra payoff whose value is between the payoff of mutual cooperation and the value of temptation to defect. Thus, this mechanism reflects that the dependency relation is stronger than the relation of ordinary mutual cooperation, but it is not large enough to cause the defection of the dependency pair. We show that the dependence of individuals hinders, promotes and never affects the cooperation on regular ring networks, square lattice, random and scale-free networks, respectively. The results for the square lattice and regular ring networks are demonstrated by the pair approximation. PMID:25798579

Evolving dynamics of trading behavior based on coordination game in complex networks

NASA Astrophysics Data System (ADS)

Bian, Yue-tang; Xu, Lu; Li, Jin-sheng

2016-05-01

This work concerns the modeling of evolvement of trading behavior in stock markets. Based on the assumption of the investors' limited rationality, the evolution mechanism of trading behavior is modeled according to the investment strategy of coordination game in network, that investors are prone to imitate their neighbors' activity through comprehensive analysis on the risk dominance degree of certain investment behavior, the network topology of their relationship and its heterogeneity. We investigate by mean-field analysis and extensive simulations the evolution of investors' trading behavior in various typical networks under different risk dominance degree of investment behavior. Our results indicate that the evolution of investors' behavior is affected by the network structure of stock market and the effect of risk dominance degree of investment behavior; the stability of equilibrium states of investors' behavior dynamics is directly related with the risk dominance degree of some behavior; connectivity and heterogeneity of the network plays an important role in the evolution of the investment behavior in stock market.

Stochastic Local Search for Core Membership Checking in Hedonic Games

NASA Astrophysics Data System (ADS)

Keinänen, Helena

Hedonic games have emerged as an important tool in economics and show promise as a useful formalism to model multi-agent coalition formation in AI as well as group formation in social networks. We consider a coNP-complete problem of core membership checking in hedonic coalition formation games. No previous algorithms to tackle the problem have been presented. In this work, we overcome this by developing two stochastic local search algorithms for core membership checking in hedonic games. We demonstrate the usefulness of the algorithms by showing experimentally that they find solutions efficiently, particularly for large agent societies.

Impact of shill intervention on the evolution of cooperation

NASA Astrophysics Data System (ADS)

Sun, Changhao; Duan, Haibin

2015-09-01

The practical significance of effective intervention in collective behavior has its roots not only in frequent migration in the modern society, but also in the actual demands of real-world applications for system efficiency improvement. Within the framework of soft control, this paper focuses on an evolutionary public goods game staged on a scale free network and explores the dependence of the evolution of cooperation on the intervention of a fraction of shills, who follow the Fixed-Cost-per-Player paradigm while the locals follow the Fixed-Cost-per-Game paradigm. We demonstrate that higher cooperation levels and better social welfare could be simultaneously induced by tuning the distribution coefficient α, where desirable outcomes are associated with large α > 0 for tense dilemmas while small α < 0 leads to satisfactory results when the enhancement factor γ increases. Moreover, we observe a transition of the composition of equilibrium cooperators from full dominance of shills to co-existence of shills and locals, and the boundary has a positive correlation with α. These results are somehow affected when we attenuate the heterogeneity of the network by relating individual fitness to payoffs averaged over its connectivity. Our findings may not only shed some light on the mechanism behind the evolution of cooperation from the perspective of external intervention, but also provide a feasible way to effectively intervene in the evolutionary outcomes of negative scenarios.

Control Theoretic Modeling for Uncertain Cultural Attitudes and Unknown Adversarial Intent

DTIC Science & Technology

2009-02-01

Constructive computational tools. 15. SUBJECT TERMS social learning, social networks , multiagent systems, game theory 16. SECURITY CLASSIFICATION OF: a...over- reactionary behaviors; 3) analysis of rational social learning in networks : analysis of belief propagation in social networks in various...general methodology as a predictive device for social network formation and for communication network formation with constraints on the lengths of

Homophyly/Kinship Model: Naturally Evolving Networks

NASA Astrophysics Data System (ADS)

Li, Angsheng; Li, Jiankou; Pan, Yicheng; Yin, Xianchen; Yong, Xi

2015-10-01

It has been a challenge to understand the formation and roles of social groups or natural communities in the evolution of species, societies and real world networks. Here, we propose the hypothesis that homophyly/kinship is the intrinsic mechanism of natural communities, introduce the notion of the affinity exponent and propose the homophyly/kinship model of networks. We demonstrate that the networks of our model satisfy a number of topological, probabilistic and combinatorial properties and, in particular, that the robustness and stability of natural communities increase as the affinity exponent increases and that the reciprocity of the networks in our model decreases as the affinity exponent increases. We show that both homophyly/kinship and reciprocity are essential to the emergence of cooperation in evolutionary games and that the homophyly/kinship and reciprocity determined by the appropriate affinity exponent guarantee the emergence of cooperation in evolutionary games, verifying Darwin’s proposal that kinship and reciprocity are the means of individual fitness. We propose the new principle of structure entropy minimisation for detecting natural communities of networks and verify the functional module property and characteristic properties by a healthy tissue cell network, a citation network, some metabolic networks and a protein interaction network.

Homophyly/Kinship Model: Naturally Evolving Networks

PubMed Central

Li, Angsheng; Li, Jiankou; Pan, Yicheng; Yin, Xianchen; Yong, Xi

2015-01-01

It has been a challenge to understand the formation and roles of social groups or natural communities in the evolution of species, societies and real world networks. Here, we propose the hypothesis that homophyly/kinship is the intrinsic mechanism of natural communities, introduce the notion of the affinity exponent and propose the homophyly/kinship model of networks. We demonstrate that the networks of our model satisfy a number of topological, probabilistic and combinatorial properties and, in particular, that the robustness and stability of natural communities increase as the affinity exponent increases and that the reciprocity of the networks in our model decreases as the affinity exponent increases. We show that both homophyly/kinship and reciprocity are essential to the emergence of cooperation in evolutionary games and that the homophyly/kinship and reciprocity determined by the appropriate affinity exponent guarantee the emergence of cooperation in evolutionary games, verifying Darwin’s proposal that kinship and reciprocity are the means of individual fitness. We propose the new principle of structure entropy minimisation for detecting natural communities of networks and verify the functional module property and characteristic properties by a healthy tissue cell network, a citation network, some metabolic networks and a protein interaction network. PMID:26478264

Designing Personalized Learning Products for Middle School Mathematics: The Case for Networked Learning Games

ERIC Educational Resources Information Center

Evans, Michael A.; Pruett, Jordan; Chang, Mido; Nino, Miguel

2014-01-01

Middle school mathematics education is subject to ongoing reform based on advances in digital instructional technologies, especially learning games, leading to recent calls for investment in "personalized learning." Through an extensive literature review, this investigation identified three priority areas that should be taken into…

Dynamic game balancing implementation using adaptive algorithm in mobile-based Safari Indonesia game

NASA Astrophysics Data System (ADS)

Yuniarti, Anny; Nata Wardanie, Novita; Kuswardayan, Imam

2018-03-01

In developing a game there is one method that should be applied to maintain the interest of players, namely dynamic game balancing. Dynamic game balancing is a process to match a player’s playing style with the behaviour, attributes, and game environment. This study applies dynamic game balancing using adaptive algorithm in scrolling shooter game type called Safari Indonesia which developed using Unity. The game of this type is portrayed by a fighter aircraft character trying to defend itself from insistent enemy attacks. This classic game is chosen to implement adaptive algorithms because it has quite complex attributes to be developed using dynamic game balancing. Tests conducted by distributing questionnaires to a number of players indicate that this method managed to reduce frustration and increase the pleasure factor in playing.

Characteristics of Internet use in relation to game genre in Korean adolescents.

PubMed

Lee, Moon-Soo; Ko, Young-Hoon; Song, Hyoung-Seok; Kwon, Ku-Hyung; Lee, Hyeon-Soo; Nam, Min; Jung, In-Kwa

2007-04-01

As the number of internet users increases, a new game genre using the internet as a networking tool is emerging. Some game genres are regarded as having greater addiction potentials than others. Games and the internet are closely related. We investigated games frequently used by adolescents and classified each of them with the help of game professionals. We also examined internet use patterns to identify relationships between game genre and internet use patterns. 627 middle school and high school students (male 488, female 139) completed questionnaires concerning computer and game use patterns and Korean internet addiction scales. Game genres were divided into eight criteria (simulation, role playing game, web board, community, action, adventure, shooting, and sports). Using Korean internet addiction scales, 627 participants were divided into a normal group (474), a potential risk group (128), and a high-risk group (25). Each group showed significant differences in total internet addiction scores. We classified players into specific game users based upon the game types they most prefer. Role playing game users showed significantly higher internet addiction scores than web board and sports game users. Game and internet addictions are also connected with interpersonal relationship patterns. We suggest that users of some game genre have unique psychological addiction potentials that are different from others and that this influences both game selection and internet use.

The neural processing of voluntary completed, real and virtual violent and nonviolent computer game scenarios displaying predefined actions in gamers and nongamers.

PubMed

Regenbogen, Christina; Herrmann, Manfred; Fehr, Thorsten

2010-01-01

Studies investigating the effects of violent computer and video game playing have resulted in heterogeneous outcomes. It has been assumed that there is a decreased ability to differentiate between virtuality and reality in people that play these games intensively. FMRI data of a group of young males with (gamers) and without (controls) a history of long-term violent computer game playing experience were obtained during the presentation of computer game and realistic video sequences. In gamers the processing of real violence in contrast to nonviolence produced activation clusters in right inferior frontal, left lingual and superior temporal brain regions. Virtual violence activated a network comprising bilateral inferior frontal, occipital, postcentral, right middle temporal, and left fusiform regions. Control participants showed extended left frontal, insula and superior frontal activations during the processing of real, and posterior activations during the processing of virtual violent scenarios. The data suggest that the ability to differentiate automatically between real and virtual violence has not been diminished by a long-term history of violent video game play, nor have gamers' neural responses to real violence in particular been subject to desensitization processes. However, analyses of individual data indicated that group-related analyses reflect only a small part of actual individual different neural network involvement, suggesting that the consideration of individual learning history is sufficient for the present discussion.

SURVIVABILITY THROUGH OPTIMIZING RESILIENT MECHANISMS (STORM)

DTIC Science & Technology

2017-04-01

STATEMENT Approved for Public Release; Distribution Unlimited. PA# 88ABW-2017-0894 Date Cleared: 07 Mar 2017 13. SUPPLEMENTARY NOTES 14. ABSTRACT Game ...quantitatively about cyber-attacks. Game theory is the branch of applied mathematics that formalizes strategic interaction among intelligent rational agents...mechanism based on game theory. This work has applied game theory to numerous cyber security problems: cloud security, cyber threat information sharing

Predictive Game Theory

NASA Technical Reports Server (NTRS)

Wolpert, David H.

2005-01-01

Probability theory governs the outcome of a game; there is a distribution over mixed strat.'s, not a single "equilibrium". To predict a single mixed strategy must use our loss function (external to the game's players. Provides a quantification of any strategy's rationality. Prove rationality falls as cost of computation rises (for players who have not previously interacted). All extends to games with varying numbers of players.

Performance of Soldiers on the Battle Sight Tank Gunnery Video Game

DTIC Science & Technology

1986-06-01

The purpose of this research was to examine practice effects on a tank gunnery video game in a series of three experiments. Number of hits and number...the standard video game with three lives and 60 rounds of ammunition, (b) a revised format that equally distributed the three lives and 60 rounds of ammunition into three separate games.