The Ex-Gaussian distribution as a model of first-person shooter game traffic

In much of the literature the extreme distribution has been used to model first-person shooter (FPS) game packet length distributions. In this paper we show that a skewed mixture distribution, the Ex-Gaussian, is also suitable for modelling the packet payload lengths for two-player games of seven popular FPS games in the server-to-client direction. Also there is a plausible physical justification for the choice of a mixture distribution as a suitable model. The Ex-Gaussian distribution has properties that can be exploited to synthesise the server-to-client packet payload length distributions for larger numbers of players using measurements taken from game trials with a small number of players. We have also outlined a computationally simple technique that can be used to synthesise FPS game server-to-client packet payload length distributions for N-players from measurements from two-player games. This technique is useful for building realistic traffic models for FPS game traffic that can be used in simulation studies.     

(A)Social reputation: Exploring the relationship between online video game involvement and social competence

Affordable and accessible Internet has changed the way video games are played, allowing individuals to connect worldwide in shared gaming spaces. On the surface participation within these environments may seem socially beneficial, as these highly social, playful spaces allow players to connect, interact with, and learn from others. However, there is a growing concern that increased participation within online gaming environments comes with a wide variety of social consequences, contributing to numerous losses in ‘offline’ sociability. While considerable research has examined these claims, consistent relationships between social competence and online video game involvement have yet to be established. The current work (N = 515) aimed to examine the extent to which online video game involvement may support, or undermine, the development and maintenance of traditional social skills. The results indicate that there are unique relationships between social skills and video game involvement within online gaming populations. However, among online video game players, these links were not as negative or broad as hypothesized. The results of this assessment dispute the anecdotal attribution of a global level of social ineptitude amongst online video game players and provide insight into the potential effects of online video game play on skill development and maintenance.     

Noise and the magic square game

A pseudo-telepathy game is a game for two or more players for which there is no classical winning strategy, but there is a winning strategy based on sharing quantum entanglement by the players. Since it is generally very hard to perfectly implement a quantum winning strategy for a pseudo-telepathy game, quantum players are almost certain to make errors even though they use a winning strategy. After introducing a model for pseudo-telepathy games, we investigate the impact of erroneously performed unitary transformations and also of noisy measurement devices on the quantum winning strategy for the magic square game. The question of how strong both types of noise can be so that quantum players would still be better than classical ones is also dealt with.     

The accelerated k-in-a-row game

We investigate two versions of the well-known k-in-a-row game. While in the most intriguing k = 5 case the outcome of the game has been recently settled, very little is known about what happens when the rules are changed. A natural modification is that the players take more than one square of the board per move in order to speed up the game. Our main goal is to improve the quadratic bound on the error term, given by Csirmaz in Csirmaz (Discrete Math. 29 (1980) 19–23), to a logarithmic one for the accelerated k-in-a-row. The other issue is the extreme sensitivity of k-in-a-row under biased rules. Beck proposed in Beck (unpublished lecture notes) that a player may trade some of his freedom of choice for the right of taking more squares than his opponent. We prove logarithmic bounds on the error term in that case, too.     

A mobile game as a support tool for children with severe difficulties in reading and spelling

We used a randomized controlled trial to investigate if a mobile game, GraphoLearn (GL), could effectively support the learning of first graders (N = 70), who have severe difficulties in reading and spelling. We studied the effects of two versions of the game: GL Reading, which focused on training letter-sound correspondence and word reading; and GL Spelling, which included additional training in phonological skills and spelling. During the spring of first grade, the children trained with tablet computers which they could carry with them during the six-week intervention. The average exposure time to training was 5 hr 44 min. The results revealed no differences in the development of reading or spelling skills between GL players and the control group. However, pre-training self-efficacy moderated the effect among GL Reading players: children with high self-efficacy developed more than the control group in word reading fluency, whereas children with low self-efficacy developed less than the control group in spelling.     

时间尺度与选择倾向性协同作用下的演化博弈模型

针对合作行为的涌现与维持问题，基于演化博弈理论和网络理论，提出了一种促进合作的演化博弈模型。该模型同时将时间尺度、选择倾向性引入到演化博弈中。在初始化阶段，根据持有策略的时间尺度将个体分为两种类型：一种个体在每个时间步都进行策略更新；另一种个体在每一轮博弈后，以某种概率来决定是否进行策略更新。在策略更新阶段，模型用个体对周围邻居的贡献来表征他的声誉，并假设参与博弈的个体倾向于学习具有较好声誉邻居的策略。仿真实验结果表明，所提出的时间尺度与选择倾向性协同作用下的演化博弈模型中，合作行为能够在群体中维持；惰性个体的存在不利于合作的涌现，但是个体的非理性行为反而能够促进合作。     

On game theoretic DSA-driven MAC for cognitive radio networks

The game theoretic dynamic spectrum allocation (DSA) technique is an efficient approach to coordinate cognitive radios sharing the spectrum. However, existing game based DSA algorithms lack a platform to support the game process. On the other hand, existing medium access control (MAC) protocols for cognitive radio networks do not fully utilize the adaptability and intelligence of the cognitive radio (CR) to achieve efficient spectrum utilization, let alone fairness and QoS support. Therefore it is necessary to develop DSA-driven MAC protocols with the game theoretic DSA embedded into the MAC layer. In this paper, based on the analysis of challenges for the game theoretic DSA in realistic applications, we conclude that a unified game theoretic DSA-driven MAC framework should constitute of four integral components: (1) DSA algorithm, deriving the spectrum access strategy for data communication; (2) negotiation mechanism, coordinating players to follow the right game policy; (3) clustering algorithm, limiting the negotiation within one cluster for scalability; (4) collision avoidance mechanism, eliminating collisions among clusters. With our MAC framework, DSA-driven MAC protocols can be conveniently developed, as illustrated in the design process of a concrete QoSe-DSA-driven MAC protocol. The game theoretic DSA-driven MAC framework can fulfill merits of game theoretic DSA algorithms including high spectrum utilization, collision-free channel access for data communication, QoS and fairness support. Through simulations, the merits of the DSA-driven MAC framework are demonstrated.     

Fuzzy AHP for determining the key features and cognitive differences of mobile game development among designer and game player

Previous studies have assessed the elements of a game design from game players’ viewpoints. Scant research has been conducted from the perspectives of both game players and game developers. This study explored the cognitive difference among game players and game developers in the importance of online game designs by employing the fuzzy analytic hierarchy process (FAHP) to analyze the importance of puzzle game designs. The online game design hierarchical framework comprising 3 systems, 9 components, and 29 factors was established. The research findings are summarized as follows: 1) System quality is the most crucial design component. 2) Game development should primarily focus on technology followed by aesthetics. 3) A gap exists in the perception of game players and game developers on the design component “service quality.” Finally, researchers can adopt the multiple criteria decision-making model used in this current study to rank the importance of design contents for cultural and creative industries.     

Social gaming,lonely life? The impact of digital game play on adolescents’ social circles

In recent years, there have been rising concerns about the impact of online video game play on users’ socialization, particularly among adolescent players. The current study addresses one of these concerns and evaluates the potential impact of social displacement on the size and quality of users’ social circles due to video game play. Using a representative sample of adolescent players, the results provide support for the emergence of social displacement effects. Increased social online video game play, but not social offline video game play, was found to correspond with smaller, and lower quality, offline social circles. However, further research is needed to assess the impact of these declines on everyday socialization, such its potential negative influence on the development and maintenance of social skills.     

The role of information in the cop-robber game

We investigate the role of the information available to the players on the outcome of the cops and robbers game. This game takes place on a graph and players move along the edges in turns. The cops win the game if they can move onto the robber’s vertex. In the standard formulation, it is assumed that the players can “see” each other at all times. A graph G$G$ is called cop-win if a single cop can capture the robber on G$G$. We study the effect of reducing the cop’s visibility. On the positive side, with a simple argument, we show that a cop with small or no visibility can capture the robber on any cop-win graph (even if the robber still has global visibility). On the negative side, we show that the reduction in cop’s visibility can result in an exponential increase in the capture time. Finally, we start the investigation of the variant where the visibility powers of the two players are symmetrical. We show that the cop can establish eye contact with the robber on any graph and present a sufficient condition for capture. In establishing this condition, we present a characterization of graphs on which a natural greedy pursuit strategy suffices for capturing the robber.     

Altruistic behavior in a nonantagonistic positional differential game

We consider a two-person nonantagonistic positional differential game (NPDG) whose dynamics is described by an ordinary nonlinear vector differential equation. Constraints on values of players’ controls are geometric. Final time of the game is fixed. Payoff functionals of both players are terminal. The formalization of positional strategies in an NPDG is based on the formalization and results of the general theory of antagonistic positional differential games (APDGs) (see monographs by N.N. Krasovskii and A.I. Subbotin [3, 4]). Additionally, in the present paper we assume that each player, together with the usual, normal (nor), type of behavior aimed at maximizing his own functional, can use other behavior types introduced in [2, 5]. In particular, these may be altruistic (alt), aggressive (agg), and paradoxical (par) types. It is assumed that in the course of the game players can switch their behavior from one type to another. Using the possibility of such switches in a repeated bimatrix 2 × 2 game in [5, 6] allowed to obtain new solutions of this game. In the present paper, extension of this approach to NPDGs leads to a new formulation of the problem. In particular, of interest is the question of how players’ outcomes at Nash solutions are transformed. An urgent problem is minimizing the time of “abnormal” behavior while achieving a good result. The paper proposes a formalization of an NPDG with behavior types (NPDGwBT). It is assumed that in an NPDGwBT each player, simultaneously with choosing a positional strategy, chooses also his own indicator function defined on the whole game horizon and taking values in the set {normal, altruistic, aggressive, paradoxical}. The indicator function of a player shows the dynamics of changes in the behavior type demonstrated by the player. Thus, in this NPDGwBT each player controls the choice of a pair {positional strategy, indicator function}. We define the notion of a BT-solution of such a game. It is expected that using behavior types in the NPDGwBT which differ from the normal one (so-called abnormal types) in some cases may lead to more favorable outcomes for the players than in the NPDG. We consider two examples of an NPDGwBT with simple dynamics in the plane in each of which one player keeps to altruistic behavior type over some time period. It is shown that in the first example payoffs of both players increase on a BT-solution as compared to the game with the normal behavior type, and in the second example, the sum of players’ payoffs is increased.     

Self-regulation influence on game play flow state

The authors use the Music Flow digital game with 266 Taiwanese junior high school students to investigate the influence of digital game player self-regulation (SR) on game flow state. Game data were used to probe various aspects of Bandura's (1986) SR learning model and related effects on game flow state as described in Csikszentmihalyi's (1990) flow theory to determine if game information can be used to measure SR during different flow states. A tool for recording stage selection, hit rate, and other real time data was created to monitor and measure flow state among players immersed in interactive play. Self-reaction capabilities were measured in terms of skill- and game-level difficulty during different states. Results indicate that SR exerted a significant and positive effect on flow state. Our main conclusions are (a) flow state was continuously influenced by self-reaction over time; (b) hit rate served as an indicator of self-judgment in terms of challenge, skill and flow state; and (c) flow states in players with distinct self-reaction capabilities were influenced by play stage selection. It is our hope that the method used in this study will help researchers in their efforts to measure and/or analyze player sense of fun in game-based learning environments.     

On a game with perfect information and time-claiming alternatives

This paper considers a new model of multistage games with perfect information in which players can control decision-making time. At each stage of the game, players choose a certain alternative from a finite set of basic alternatives and also time necessary to realize this basic alternative. The payoffs of players depend on the game path defined by the chosen alternatives and also on the time to realize this path at each stage. We use the subgame-perfect ε-Nash equilibrium as the optimality principle of the model. This paper is a continuation of the earlier research [5].     

Characterizing the Nash equilibria of a three-player Bayesian quantum game

Quantum games with incomplete information can be studied within a Bayesian framework. We consider a version of prisoner’s dilemma (PD) in this framework with three players and characterize the Nash equilibria. A variation of the standard PD game is set up with two types of the second prisoner and the first prisoner plays with them with probability p and \(1-p\), respectively. The Bayesian nature of the game manifests in the uncertainty that the first prisoner faces about his opponent’s type which is encoded either in a classical probability or in the amplitudes of a wave function. Here, we consider scenarios with asymmetric payoffs between the first and second prisoner for different values of the probability, p, and the entanglement. Our results indicate a class of Nash equilibria (NE) with rich structures, characterized by a phase relationship on the strategies of the players. The rich structure can be exploited by the referee to set up rules of the game to push the players toward a specific class of NE. These results provide a deeper insight into the quantum advantages of Bayesian games over their classical counterpart.     

“She is just stupid”—Analyzing user–agent interactions in emotional game situations

A multiplayer dice game was realized which is played by two users and one embodied conversational agent. During the game, the players have to lie to each other to win the game and the longer the game commences the more probable it is that someone is lying, which creates highly emotional situations. We ran a number of evaluation studies with the system. The specific setting allows us to compare user–user interactions directly with user–agent interactions in the same game. So far, the users’ gaze behavior and the users’ verbal behavior towards one another and towards the agent have been analyzed. Gaze and verbal behavior towards the agent partly resembles patterns found in the literature for human–human interactions, partly the behavior deviates from these observations and could be interpreted as rude or impolite like continuous staring, insulting, or talking about the agent. For most of these seemingly abusive behaviors, a more thorough analysis reveals that they are either acceptable or present some interesting insights for improving the interaction design between users and embodied conversational agents.     

Match+Guardian: a secure peer-to-peer trading card game protocol

In trading card games (TCGs), players create a deck of cards from a subset of all cards in the game to compete with other players. While online TCGs currently exist, these typically rely on a client/server architecture and require clients to be connected to the server at all times. Instead, we propose, analyze and evaluate Match+Guardian (M+G), our secure peer-to-peer protocol for implementing online TCGs. We break down actions common to all TCGs and explain how they can be executed between two players without the need for a third party referee (which usually requires an unbiased server). In each action, the player is either prevented from cheating or if they do cheat, the opponent will be able to prove they have done so. We show these methods are secure and may be shuffled into new styles of TCGs. We then measure moves in a real trading card game to compare to our implementation of M+G and conclude with an evaluation of its performance on the Android^TM platform, demonstrating that M+G can be used in a peer-to-peer fashion on mobile devices.     

Application of reinforcement learning to the game of Othello

Operations research and management science are often confronted with sequential decision making problems with large state spaces. Standard methods that are used for solving such complex problems are associated with some difficulties. As we discuss in this article, these methods are plagued by the so-called curse of dimensionality and the curse of modelling. In this article, we discuss reinforcement learning, a machine learning technique for solving sequential decision making problems with large state spaces. We describe how reinforcement learning can be combined with a function approximation method to avoid both the curse of dimensionality and the curse of modelling. To illustrate the usefulness of this approach, we apply it to a problem with a huge state space—learning to play the game of Othello. We describe experiments in which reinforcement learning agents learn to play the game of Othello without the use of any knowledge provided by human experts. It turns out that the reinforcement learning agents learn to play the game of Othello better than players that use basic strategies.     

Player target tracking and detection in football game video using edge computing and deep learning

The purpose is to explore the player detection and motion tracking in football game video based on edge computing and deep learning (DL), thus improving the detection effect of player trajectory in different scenes. First, the basic technology of player target tracking and detection task is analyzed based on the Histograms of Oriented Gradients feature. Then, the neural network structure in DL is combined with the target tracking method to improve the miss detection problem of the Faster R-CNN (FRCN) algorithm in detecting small targets. Edge computing places massive computing nodes close to the terminal devices to meet the high computing and low latency requirements of DL on edge devices. After the occlusion problem in the football game is analyzed, the optimized algorithm is applied to the public dataset OTB2013 and the football game dataset containing 80 motion trajectories. After testing, the target tracking accuracy of the improved FRCN is 89.1%, the target tracking success rate is 64.5%, and the running frame rate is still about 25 fps. The high confidence of FRCN algorithm also avoids template pollution. In the ordinary scene, the FRCN algorithm basically does not lose the target. The area under curve value of the proposed FRCN algorithm decreases slightly in the scene where the target is occluded. The FRCN algorithm based on DL technology can achieve the target tracking of players in football game video and has strong robustness to the situation of players occlusion. The designed target detection algorithm is applied to the football game video, which can better analyze the technical characteristics of players, promote the development of football technology, bring different viewing experiences to the audience, drive the development of economic products derived from football games, and promote the dissemination and promotion of football.