Two-stage network games

In the paper, two-stage network games are studied. At the first stage of the game, the players form a network, while at the second stage they choose strategies according to the network realized at the first stage. Both noncooperative and cooperative settings are considered. In the noncooperative case, the Nash equilibrium is used as a solution concept, whereas the cooperative setting involves an allocation (the Shapley value) as a solution concept. It is demonstrated that the Shapley value does not satisfy the time consistency property.     

Stability and interaction in flatline games

Starting from a given one-shot game played by a finite population of agents living in flatline, a circular or constrained grid structured by the classical definitions of neighborhood, we define transformation rules for cellular automata, which are determined by the best-reply behavior in standard two-person symmetric matrix games.     

Power in threshold network flow games

Preference aggregation is used in a variety of multiagent applications, and as a result, voting theory has become an important topic in multiagent system research. However, power indices (which reflect how much “real power” a voter has in a weighted voting system) have received relatively little attention, although they have long been studied in political science and economics. We consider a particular multiagent domain, a threshold network flow game. Agents control the edges of a graph; a coalition wins if it can send a flow that exceeds a given threshold from a source vertex to a target vertex. The relative power of each edge/agent reflects its significance in enabling such a flow, and in real-world networks could be used, for example, to allocate resources for maintaining parts of the network. We examine the computational complexity of calculating two prominent power indices, the Banzhaf index and the Shapley-Shubik index, in this network flow domain. We also consider the complexity of calculating the core in this domain. The core can be used to allocate, in a stable manner, the gains of the coalition that is established. We show that calculating the Shapley-Shubik index in this network flow domain is NP-hard, and that calculating the Banzhaf index is #P-complete. Despite these negative results, we show that for some restricted network flow domains there exists a polynomial algorithm for calculating agents’ Banzhaf power indices. We also show that computing the core in this game can be performed in polynomial time.     

Multistage network games with perfect information

We consider multistage network games with perfect information. At each time instant, a current network structure connecting the players is specified. It is assumed that each edge has some utility value (player’s benefit from being linked to another player), and players can change the network structure at each stage. We propose a method for finding optimal behavior for players in games of this type.     

Dynamics and stability of potential hyper-networked evolutionary games

This paper considers the modeling and convergence of hyper-networked evolutionary games (HNEGs). In an HNEG the network graph is a hypergraph, which allows the fundamental network game to be a multi-player one. Using semi-tensor product of matrices and the fundamental evolutionary equation, the dynamics of an HNEG is obtained and we extend the results about the networked evolutionary games to show whether an HNEG is potential and how to calculate the potential. Then we propose a new strategy updating rule, called the cascading myopic best response adjustment rule (MBRAR), and prove that under the cascading MBRAR the strategies of an HNEG will converge to a pure Nash equilibrium. An example is presented and discussed in detail to demonstrate the theoretical and numerical results.     

Sonification and interaction design in computer games for visually impaired individuals

Multimedia Tools and Applications - Video games are changing how we interact and communicate with each other. They can provide an authentic and collaborative platform for building new communities...     

Affective interaction: Using emotions as a user interface in games

Affective computing, as a novel paradigm, adds a new feature into the human-computer interactions era that brings emotions into the process of design and evaluation. Such condition influences digital games’ not only structural dimension but also content and evaluation areas. This study aims to evaluate the effect of using emotions in the form of facial expressions as a User Interface (UI) and the input of a system in virtual scenarios. After studying the findings and methods of previous researches, a conceptual framework for Affective User Interface Design and Evaluation (AFFUIDE) has been proposed. Then, a game in the genre of shoot ‘em up (called Facial Battle) in four interaction modes has been developed. The evaluation of this study has been performed in terms of the players’ performance and experience. For this purpose, 18 male students of the Multimedia Faculty of Tabriz Islamic Art University took part in the experiments, who were asked to play all four modes of the game. Then, after analyzing the normalization of collected data, one-way ANOVA and U Mann Whitney tests were used for the statistical analysis. The findings indicate that the Traditional UI is the most usable and the Full Affective UI has the best sense of fun and user experience among other methods. However, the hybrid mode (affective shooting), is not only usable as traditional mode, but it also works better in terms of user experience compared to other modes.

     

Managing network security — Part 6: Computer games and network security management

Over the last few years, computing has changed to an almost purely networked environment, but the technical aspects of information protection have not kept up. As a result, the success of information security programmes has increasingly become a function of our ability to make prudent management decisions about organizational activities. This series of articles takes a management view of protection and seeks to reconcile the need for security with the limitations of technology.     

Characterizing game dynamics in two-player strategy games using network motifs.

Many complex systems, whether biological, sociological, or physical ones, can be represented using networks. In these networks, a node represents an entity, and an arc represents a relationship/constraint between two entities. In discrete dynamics, one can construct a series of networks with each network representing a time snapshot of interaction among the different components in the system. Understanding these networks is a key to understand the dynamics of real and artificial systems. Network motifs are small graphs-usually three to four nodes-representing local structures. They have been widely used in studying complex systems and in characterizing features on the system level by analyzing locally how the substructures are formed. Frequencies of different network motifs have been shown in the literature to vary from one network to another, and conclusions hypothesized that these variations are due to the evolution/dynamics of the system. In this paper, we show for the first time that in strategy games, each game (i.e., type of dynamism) has its own signature of motifs and that this signature is maintained during the evolution of the game. We reveal that deterministic strategy games have unique footprints (motifs' count) that can be used to recognize and classify the game's type and that these footprints are consistent along the evolutionary path of the game. The findings of this paper have significance for a wide range of fields in cybernetics.     

脉冲神经网络算法及其在扑克游戏中的应用

随着人工智能的发展,目前主流的神经网络面临着计算量大、功耗高、智能化程度低等问题.为解决以上问题,根据人脑的特性,提出具有普适性的多层脉冲神经网络结构,利用生物学的因果律提出脉冲神经网络算法.通过控制引导神经元的激活时间间接调整目标权值,将算法应用在扑克游戏中,使扑克机器人能够学习一个人的打牌能力,实现拟人化程度为...     

Video game values: Human–computer interaction and games

Current human–computer interaction (HCI) research into video games rarely considers how they are different from other forms of software. This leads to research that, while useful concerning standard issues of interface design, does not address the nature of video games as games specifically. Unlike most software, video games are not made to support external, user-defined tasks, but instead define their own activities for players to engage in. We argue that video games contain systems of values which players perceive and adopt, and which shape the play of the game. A focus on video game values promotes a holistic view of video games as software, media, and as games specifically, which leads to a genuine video game HCI.     

基于J2ME技术的手机网络游戏研究与开发

探讨了一种能将移动手机网络游戏管理平台和内容相互分离,并在应用中根据需要进行组合的通用移动网络游戏系统的设计。手机游戏开发基于J2ME技术基础,以牌类游戏为实例,采用了MVC框架模式进行设计,提高了系统的可维护性,有利于系统的二次开发;基于Java的特性使该系统具有较高的可移植性,可在主流手机平台中正常运行,减少移植成本。     

使用长短期记忆网络预测NBA比赛胜负

深度学习与机器学习的方法已广泛应用于NBA(美国篮球职篮联赛)的比赛胜负的预测中,然而过去的方法未对过去几场比赛的数据进行建模,忽略了比赛双方近期状态的有效表示.为了解决这个问题,提出了基于长短期记忆(LSTM)网络的方法对NBA常规赛的比赛胜负进行预测.该方法分别以比赛中的两支球队过去几场比赛的数据作为LSTM的输入,以该场比赛结果作为输出,训练能够预测比赛胜负的模型.本质上是使用球队在该赛季的历史数据的平均值作为该球队的实力,以近几场比赛的数据序列作为该球队状态的体现.在实验中比较了其他几种预测NBA比赛胜负的方法(支持向量机、卷积神经网络、逻辑回归模型等方法),数据来自2014—2019年间的5个赛季的NBA常规赛数据.结果表明,模型的预测准确率达到(69.09％),高于其他几种模型.     

使用长短期记忆网络预测NBA比赛胜负

深度学习与机器学习的方法已广泛应用于NBA(美国篮球职篮联赛)的比赛胜负的预测中,然而过去的方法未对过去几场比赛的数据进行建模,忽略了比赛双方近期状态的有效表示.为了解决这个问题,提出了基于长短期记忆(LSTM)网络的方法对NBA常规赛的比赛胜负进行预测.该方法分别以比赛中的两支球队过去几场比赛的数据作为LSTM的输入,以该场比赛结果作为输出,训练能够预测比赛胜负的模型.本质上是使用球队在该赛季的历史数据的平均值作为该球队的实力,以近几场比赛的数据序列作为该球队状态的体现.在实验中比较了其他几种预测NBA比赛胜负的方法(支持向量机、卷积神经网络、逻辑回归模型等方法),数据来自2014—2019年间的5个赛季的NBA常规赛数据.结果表明,模型的预测准确率达到(69.09％),高于其他几种模型.     

Neural network guidance based on pursuit-evasion games with enhanced performance

This paper addresses a neural network guidance based on pursuit-evasion games, and performance enhancing methods for it. Two-dimensional pursuit-evasion games solved by the gradient-based method are considered. The neural network guidance law employs the range, range rate, line-of-sight rate, and heading error as its input variables. Additional pattern selection methods and a hybrid guidance method are proposed for the sake of the interception performance enhancement. Numerical simulations are accompanied for the verification of the neural network approximation, and of the improved interception performance by the proposed methods. Moreover, all proposed guidance laws are compared with proportional navigation.     

Dynamics of weak interaction in systems of similar species

The dynamics of a system that describes the interaction between two similar species are studied. A normal form that is reduced to a normal form of the system of diffused weakly connected Hutchinson equations is constructed.     

Dependence in games and dependence games

In the multi-agent systems community, dependence theory and game theory are often presented as two alternative perspectives on the analysis of agent interaction. The paper presents a formal analysis of a notion of dependence between players, given in terms of standard game-theoretic notions of rationality such as dominant strategy and best response. This brings the notion of dependence within the realm of game theory providing it with the sort of mathematical foundations which still lacks. Concretely, the paper presents two results: first, it shows how the proposed notion of dependence allows for an elegant characterization of a property of reciprocity for outcomes in strategic games; and second, it shows how the notion can be used to define new classes of coalitional games, where coalitions can force outcomes only in the presence of reciprocal dependencies.     

基于蛋白质相互作用网络的聚类算法研究

蛋白质相互作用网络是计算机科学技术的一个新研究领域。蛋白质相互作用网络中结点之间的距离度量需要通过基于网络的最短路径距离来重新定义,其计算代价高,这使得已有的基于欧几何距离的聚类算法不能直接运用到这种环境中。因此,通过蛋白质相互作用网络的特征提出了一种新的聚类算法。算法使用网络中的边和结点信息来缩减搜索空间,避免了一些不必要的距离计算。实验结果表明,算法对于真实的蛋白质相互作用网络中的结点聚类是高效的。     

人际信息交互中低功耗网络发现应用研究

无线人际信息交互网络围绕人际信息交互的特点展开。重点关注无线通信中的网络发现中的能耗问题,利用IEEE802.15.4网络的超帧结构,提出了一种通过变换超帧参数实现的低功耗网络发现算法,分析了该算法的能耗与时间约束的关系。最后,在硬件平台上开发了电子名片应用以测试网络发现算法的有效性。