The relationship between online game playing motivation and selection of online game characters – the case of Taiwan

The alarming growth rate in the online game industry calls for a need of understanding the determinants of online gamers’ behaviour. Investigating how online gamers choose different online characters assists online game vendors to design characters that match the needs of different online gamers. Recently, numerous online game designers have introduced celebrity figures as characters for certain online games. The popularity of those celebrities has resulted in greater awareness of these games, and hopefully further increases the playability of online games. While different online gamers are motivated by different desires for playing, it is insufficiently researched whether these online celebrity characters have actually altered players’ choice in giving preference to these games. Thus, this study conducts an experimental design to study the reasons behind players’ choice of characters by studying how online games perceive the interpersonal attractiveness of celebrity online characters, and how online gamers with different playing motivations display different behaviours in their choice of online game characters. Results from the survey filled out by participants after the experiments show that the attractiveness of celebrity online characters is significantly higher than that of non-celebrity characters. Further, online game players with a social playing motivation tend to choose celebrities as their online game characters.     

An approach for community detection in social networks based on cooperative games theory

Detecting communities is of great importance in social network analysis. However it is an issue that has not yet been satisfactorily solved, despite the efforts made by interdisciplinary research communities over the past few years, because of the nature of complexity in deciding how community structures should be recognized. In this paper we propose an approach based on cooperative game theory for community detection in social networks. We regard individuals as players, and regard communities as coalitions formed by players, and model community detection problem as the formation and optimization of coalitions. Furthermore, we define coalition profile for players to indicate coalitions that players joined, the order of a coalition profile is defined as the number of coalitions in a coalition profile, and we introduce a utility function to measure preference of coalition profiles. Accordingly, we propose an algorithm to detect a coalition profile with maximal utility function values. We have implemented the algorithms developed in this study and experimental results demonstrate the effectiveness of our approaches.     

Multi‐Unit Bayesian Auction with Demand or Budget Constraints

We consider the problem of revenue maximization on multi‐unit auctions where items are distinguished by their relative values; any pair of items has the same ratio of values to all buyers. As is common in the study of revenue maximizing problems, we assume that buyers' valuations are drawn from public known distributions and they have additive valuations for multiple items. Our problem is well motivated by sponsored search auctions, which made money for Google and Yahoo! in practice. In this auction, each advertiser bids an amount b_i to compete for ad slots on a web page. The value of each ad slot corresponds to its click‐through‐rate, and each buyer has her own per‐click valuations, which is her private information. Obviously, a strategic bidder may bid an amount that is different with her true valuation to improve her utility. Our goal is to design truthful mechanisms avoiding this misreporting. We develop the optimal (with maximum revenue) truthful auction for a relaxed demand model (where each buyer i wants at most d_i items) and a sharp demand model (where buyer i wants exactly d_i items). We also find an auction that always guarantees at least half of the revenue of the optimal auction when the buyers are budget constrained. Moreover, all of the auctions we design can be computed efficiently, that is, in polynomial time.     

Video game playing in the general adult population of Germany: Can higher gaming time of males be explained by gender specific genre preferences?

BackgroundPrior studies observed involvement with video games to vary between different sociodemographic strata with considerable higher gaming time in males compared to females. However, empirical evidence explaining the gender gap in gaming time is still scarce. The present study aims to evaluate if the higher gaming time can be attributed to gender specific game genre preferences.MethodsA nationwide representative survey comprising 3073 participants aged 16–93 years (M = 49.1; SD = 18.2) was conducted. Video game use and genre preferences were assessed via a written questionnaire. OLS regression and subsequent mediation analyses were used to determine significant predictors of gaming time and to evaluate the contribution of genre preferences.ResultsHigher age, high education and employment predicted lower gaming time whereas male gender and the preference of certain game genres predicted higher gaming time. Mediation analyses revealed that the higher gaming time of males is fully mediated by the higher preference of role-playing and shooter games among this gender group.ConclusionThe higher gaming time of men is fully accounted for by the male specific preference for certain game genres. Future research should address the functional connection between genre preferences and gaming behavior in further detail.     

A review on cost allocation methods in collaborative transportation

Collaboration in transportation between two or more agents is becoming an important approach to find efficient solutions or plans. Efficiency can be measured in, for example, lower cost or more flexibility. An important aspect of the collaboration is to decide on how to share the benefits—for example, cost, profit, or resources. There are many sharing mechanisms or cost allocations proposed in the literature. Some are based on simple proportional rules and others are based on theoretical concepts found in game theory. We provide a survey on cost allocation methods found in the literature on collaborative transportation, including problems on planning, vehicle routing, traveling salesman, distribution, and inventory. A total of 55 scientific articles compose the main part of the survey, most of them published between 2010 and 2015. We identify more than 40 cost allocation methods used in this stream of literature. We describe the theoretical basis for the main methods as well as the cases where they are used. We also report savings from the collaborations when they are based on industrial data. Some directions for future research are discussed.     

A Differential Game Based Guidance Law for an Accelerating Exoatmospheric Missile

A differential game‐based guidance law design is proposed for a class of accelerating exoatmospheric missiles. By analyzing the nonlinear dynamic equations, a class of motions that does not require maneuver effort is derived for the missile. Using this property, a two phase guidance scheme can be derived that permits a perfect interception. In Phase 1, the missile is put in collision course with the target, which means in Phase 2 the missile should intercept the target with a straight line flight course, at a specified terminal body angle. Differential game based guidance laws are derived respectively for the two phases to guarantee the implementation of the guidance scheme. Simulation results show that the methodology provides robust interception performance.     

基于收益率门槛限制考虑的网格资源拍卖问题

基于收益率门槛限制的视角,通过建立效用函数模型并结合动态博弈理论,对网格资源的拍卖问题进行了探讨.在对网格资源提供者与竞标网格资源使用者的动态博弈过程进行分析时发现,网格资源提供者的最优策略选择决定于其对货币收益与非货币收益的偏好程度,以及网格资源使用者的最高报价.在收益率门槛给定的条件下,当参与竞标的网格资源使用者具有较低的生产利润或付出较高的努力成本时,网格资源使用者将会选择价格较低的投标策略.研究结果表明收益率门槛机制的引入,在一定程度上可以使得参与双方的效用达到最大化.     

拼图游戏生成器的设计与实现

拼图游戏生成器可选择本地图片、游戏难度,自动生成简单却具有丰富趣味性的智力游戏。讨论分析了拼图游戏生成器的实现难点,运用八数码问题的算法来实现拼图的移动,通过Swing来实现图片的上载等功能。拼图游戏生成器跟传统拼图游戏相比,具有一定的灵活性、耐玩性。     

Buyer-supplier games: Optimization over the core

In a buyer-supplier game, a special type of assignment game, a distinguished player, called the buyer, wishes to purchase some combinatorial structure. A set of players, called suppliers, offer various components of the structure for sale. Any combinatorial minimization problem can be transformed into a buyer-supplier game. While most previous work has been concerned with characterizing the core of buyer-supplier games, in this paper we study optimization over the set of core vectors. We give a polynomial time algorithm for optimizing over the core of any buyer-supplier game for which the underlying minimization problem is solvable in polynomial time. In addition, we show that it is hard to determine whether a given vector belongs to the core if the base minimization problem is not solvable in polynomial time. Finally, we introduce and study the concept of focus point price, which answers the question: If we are constrained to play in equilibrium, how much can we lose by playing the wrong equilibrium?     

一种新型的认知无线电合作频谱感知算法*

为了提高认知无线电频谱感知性能,同时考虑到不同认知用户SU(Secondary User)具有不同的感知贡献和谈判力量,该文利用合作博弈理论提出了一种新的基于认知无线电的合作频谱感知非对称纳什谈判算法ANBS(Asymmetric Nash Bargaining Solution),该算法充分考虑到了每一个认知用户的感知可信度不尽相同的情况。仿真结果表明,与NBS(Nash Bargaining Solution)等算法相比,该算法不仅具有更强的合理性和可靠性,而且使系统整体感知性能得到了较大提高。