New Algorithms for Solving Simple Stochastic Games

We present new algorithms for determining optimal strategies for two-player games with proba- bilistic moves and reachability winning conditions. Such games, known as simple stochastic games, were extensively studied by A.Condon [Anne Condon. The complexity of stochastic games. Information and Computation, 96(2):203–224, 1992, Anne Condon. On algorithms for simple stochastic games. In Jin-Yi Cai, editor, Advances in Computational Complexity Theory, volume 13 of DIMACS Series in Discrete Mathematics and Theoretical Computer Science, pages 51–73. AMS, 1993]. Many interesting problems, including parity games and hence also mu-calculus model checking, can be reduced to simple stochastic games. It is an open problem, whether simple stochastic games can be solved in polynomial time. Our algorithms determine the optimal expected payoffs in the game. We use geometric interpre- tation of the search space as a subset of the hyper-cube [0,1]^N. The main idea is to divide this set into convex subregions in which linear optimization methods can be used. We show how one can proceed from one subregion to the other so that, eventually, a region containing the optinal payoffs will be found. The total number of subregions is exponential in the size of the game but, in practice, the algorithms need to visit only few of them to find a solution. We believe that our new algorithms could provide new insights into the difficult problem of deter- mining algorithmic complexity of simple stochastic games and other, equivallent problems.     

A social scientific framework for social systems in online video games: Building a better looking for raid loot system in World of Warcraft

This paper examines social behavior in the online video game World of Warcraft. Specifically focusing on one element of social design: the behavior of players in the first release of Looking-for-Raid (LFR) loot system of World of Warcraft. It uses lens of economic game theory, combined with Williams (2010) mapping principle and a modern theoretical account of human decision-making, to explore how theory about individual interactions in well-defined contexts (games) can explain collective behavior. It provides some support for this theoretical approach with an examination of data collected as part of an ethnographic study, through focus groups, and a survey distributed to 333 World of Warcraft players. It concludes with a discussion of the results and some guidelines for predicting collective outcomes in certain types of online games using the introduced framework.     

An analysis of expected-outcome

Abstract

Static evaluators have been used in every game program ever written. These heuristic functions attempt to differentiate between strong and weak moves by assigning them values based on directly detectable game features. Despite their ubiquity, evaluation functions are not well understood; the development of a theory of evaluator design has been too long coming. In fact, the general consensus is that no theory is possible, because expertise is required to develop even a simple evaluator.

One recently introduced ‘generic’ evaluation function, the expected-outcome model, proposed evaluating a node as the expected value of a game's outcome, given random play from that node on. Experimental studies conducted on evaluators designed under this model yielded encouraging results in tac-tac-toe, Othello, and chess. This paper analyzes the expected-outcome model on a simple class of game trees, and shows that the moves recommended under the assumptions of random play and perfect play are identical. This vindicates what appeared to have been an overly naive assumption, and furthers the claim that statistically interpreted evaluation functions are powerful, as well as elegant.     

基于稀疏贝叶斯算法的演化博弈网络重构

演化博弈是自然和社会系统中一种常见的互动类型,探知演化博弈网络的拓扑结构是理解其功能和集体行为的基础。对于演化博弈网络,个体的博弈行为通常难以用动力学方程进行描述,而且相关的时序信息一般数量有限并且是离散的,因此在有限的个体博弈信息下重构网络的结构有着重要的研究意义。本文基于稀疏贝叶斯学习方法进一步发展了演化博弈网络的重构方法,通过在随机网络和小世界网络上的数值模拟验证该方法的有效性。与先前的基于L1范数的方法相比,该方法同样能够在较少的个体博弈信息下实现网络的重构,并且具有更高的重构效率和更强的噪声鲁棒性。     

An activity theory-based model for serious games analysis and conceptual design

There are currently a number of models, frameworks and methodologies for serious games analysis and design that provide useful interpretations of the possibilities and limitations offered by serious games. However, these tools focus mostly on high-level aspects and requirements and do not help understand how such high-level requirements can be concretely satisfied. In this paper, we present a conceptual model, called Activity Theory-based Model of Serious Games (ATMSG), that aims to fill this gap. ATMSG supports a systematic and detailed representation of educational serious games, depicting the ways that game elements are connected to each other throughout the game, and how these elements contribute to the achievement of the desired pedagogical goals. Three evaluation studies indicate that ATMSG helped participants, particularly those with gaming experience, identify and understand the roles of each component in the game and recognize the game's educational objectives.     

奥运场馆火灾分析中软件集成方法的研究

根据奥运场馆防火安会分析的需要，研究了火灾模拟和结构分析一体化系统的集成方法，并开发了结构火灾模拟分析系统——SFSAS系统，该系统基于AutoCAD图形平台进行二次开发，通过快速建模系统和前处理模块、模型转换模块、数据共享模块以及后处理模块，将FDS和ANSYS集成，形成一个一体化拿过程的分析系统，利用该系统对奥运场馆进行火灾安全分析，可以为场馆结构的防火设计和结构安全评估提供依据。     

Geometry of Pursuit-Evasion on Second Order Rotation Surfaces

Differential games with simple motionin a game space with non-unique shortest geodesic line havephase portraits with complicated structure of singular surfaces.The successful solution of such games on a family of two-dimensionalcones [1] was based to the large extent on the parameter analysisof the problem. In the present paper the results of pursuit gameon a cone of one sheet are extended to the game on the full two-sheetcone. The latter surface is included in one-parametric familyof rotation surfaces (each of which is characterized by two moreparameters), and the game on it is considered as the generatingproblem for the analysis of the games on the perturbed surfaces.The paper continues the previous investigations of the authors.In [2], [3] some local results are obtained for the games onRiemannian manifolds. In [1], [2] the game problems are solvedfor a two-dimensional cone, in [4], [5] one sheet of a double-sheetedrotation hyperboloid is considered as game space and geometricalproperties of trajectories are analyzed.     

DIAGAL: An Agent Communication Language Based on Dialogue Games and Sustained by Social Commitments

In recent years, social commitment based approaches have been proposed to solve problems issuing from previous mentalistic based semantics for agent communication languages. This paper follows the same line of thought since it presents the latest version of our dialogue game based agent communication language – DIAlogue-Game based Agent Language (DIAGAL) – which allows agents to manipulate the public layer of social commitments through dialogue, by creating, canceling and updating their social commitments. To make apparent such commitments, we consider here Agent Communication Language (ACL) from the dialectic point of view, where agents “play a game” based on commitments. Such games based on commitments are incorporated in the DIAGAL language, which has been developed having in mind the following questions: (a) What kind of structure does the game have? How are rules specified within the game? (b) What kind of games compositions are allowed? (c) How do participants in conversations reach agreement on the current game? How are games opened or closed? Using such games we show how we can study the commitments dynamic to model agent dialogue and we present metrics that can be used to evaluate the quality of a dialogue between agents. Next, we use an example (summer festival organization) to show how DIAGAL can be used in analyzing and modeling automated conversations in offices. Finally, we present the results and analysis of the summer festival simulations that we realized through our dialogue game simulator (DGS).     

Collective Behavior of G-Type Automata

The adaptive capabilities of automata are judged primarily on the basis of their behavior in random environments (situations). One can, of course, study these properties from various points of view, but the ability of automata to participate in games, i.e., their purposive collective behavior, is of special interest. This means that we have a ν-person game, the players being given not only the rules of the game, but also any other information that may be useful, such as the strategies of all the participants. It is assumed that if this game admits a behavior which is most advantageous for all the players (“the game has a solution”), then the competent and reasonable participants will adopt this behavior.     

Reinforcement Learning Rules in a Repeated Game

This paper examines the performance of simple reinforcement learningalgorithms in a stationary environment and in a repeated game where theenvironment evolves endogenously based on the actions of other agents. Sometypes of reinforcement learning rules can be extremely sensitive to smallchanges in the initial conditions, consequently, events early in a simulationcan affect the performance of the rule over a relatively long time horizon.However, when multiple adaptive agents interact, algorithms that performedpoorly in a stationary environment often converge rapidly to a stableaggregate behaviors despite the slow and erratic behavior of individuallearners. Algorithms that are robust in stationary environments can exhibitslow convergence in an evolving environment.     

An instrument to build a gamer clustering framework according to gaming preferences and habits

In the era of digital gaming, there is a pressing need to better understand how people's gaming preferences and habits affect behavior and can inform educational game design. However, instruments available for such endeavor are rather informal and limited, lack proper evaluation, and often yield results that are hard to interpret. In this paper we present the design and preliminary validation (involving N = 754 Spanish secondary school students) of a simple instrument that, based on a 10-item Game Preferences Questionnaire (GPQ), classifies participants into four ‘clusters’ or types of gamers, allowing for easy interpretation of the results. These clusters are: (1) Full gamers, covering individuals that play all kinds of games with a high frequency; (2) Hardcore gamers, playing mostly first-person shooters and sport games; (3) Casual gamers, playing moderately musical, social and thinking games; and (4) Non-gamers, who do not usually play games of any kind. The instrument may have uses in psychology and behavioral sciences, as there is evidence suggesting that attitudes towards gaming affects personal attitudes and behavior. Besides, we propose applying the instrument to help designers of educational games to get better tailored their games to their target audiences.     

Politeness improves interactivity in dense crowds

Traversing dense crowds can be challenging, but it is especially difficult in a virtual environment where the user is limited to simple input devices. Predicting near‐future user movements with a hidden Markov model allows nearby autonomous agents to react politely, that is, to specifically avoid impeding the movement of the user. This predictive model and simple avoidance scheme are tested by six subjects in 360 short interactive games and by a 10‐participant two‐alternative forced choice questionnaire. Polite agents are found to significantly improve the player's ability to navigate quickly and without collision, and the resulting character movements showed increased naturalness for two of the three game scenarios. Copyright © 2012 John Wiley & Sons, Ltd.     

Impasse-driven learning in the context of video games

This study was designed to elucidate the problem-solving skills used by frequent and infrequent video game players to negotiate impasses encountered while playing a novel video game. All participants were instructed to think aloud while playing a video game for 20 consecutive minutes. Comments made were then used to make inferences about the problem-solving skills that participants used to resolve impasses encountered during the game. Findings showed that frequent players made significantly greater reference to insight and game strategies than infrequent players. After reaching an impasse, all players also were most likely to comment on their game progress and potential game strategies to use. Over the course of game play, all participants showed increasing emphasis on their problem-solving skills as evidenced through their greater mention of insight, game strategies, and goal comments.     

Gamifying collective human behavior with gameful digital rhetoric

This paper presents a design framework called Gameful Digital Rhetoric that offers a set of design frames for designing meaningful digital rhetoric that guides collective human behavior in ubiquitous social digital services, such as crowdsourcing. The framework is extracted from our experiences with building and developing crowdsourcing case studies. From a video game perspective, the paper has categorized our experiences into seven design frames to encourage collective human activity. This approach is different from traditional gamification, as it focuses more on the semiotic aspect of virtuality in the video games, not game mechanics; it helps to enhance the current meaning of the real world for changing human attitude and behavior through various socio-cultural and psychological techniques. Therefore, it is possible to discuss respective design frames for enhancing crowdsourcing by incrementally adding new digital rhetoric. The paper also presents how Gameful Digital Rhetoric allows us to guide collective human behavior in Collectivist Crowdsourcing; the design is explained through a scenario-based and experiment-based analyses. The paper then discusses how to design collective human behavior with Gameful Digital Rhetoric and how to identify the design’s potential pitfalls. Our approach offers useful insights into the design of future social digital services that influence collective human behavior     

Analyzing the dynamics of stigmergetic interactions through pheromone games

The concept of stigmergy provides a simple framework for interaction and coordination in multi-agent systems. However, determining the global system behavior that will arise from local stigmergetic interactions is a complex problem. In this paper we propose to use Game Theory to analyze stigmergetic interactions. We show that a system where agents coordinate by sharing local pheromone information can be approximated by a limiting pheromone game in which different pheromone vectors represent player strategies. This game view allows us to use established methods and solution concepts from game theory to describe the properties of stigmergy based systems. Our goal is to provide a new framework to aid in the understanding and design of pheromone interactions. We demonstrate how we can use this system to determine the long term system behavior of a simple pheromone model, by analyzing the convergence properties of the pheromone update rule in the approximating game. We also apply this model to cases where multiple colonies of agents concurrently optimize different objectives. In this case a limiting colony game can be linked to colony level interactions to characterize the global system behavior.     

基于XNA框架的Windows phone小型游戏的开发

电子游戏的开发是一项赋予想象力和创造力的开发活动。Windows Phone作为最新的游戏平台在未来的游戏市场中被看好。本文以一款简单有趣的横版卷轴飞行射击游戏为例,对一个基于XNA框架的、在Windows Phone上的小型游戏的开发过程做了论述。     

Motion capture controls negate the violent video-game effect

Considerable research suggests that violent video game play increases players’ aggression. However, few studies have investigated this effect in the now ubiquitous context of motion-capture technology. Study 1 used a 2 × 2 design, with a violent (Soul Calibur) and non-violent (Lego Indiana Jones) game, played under analog (Playstation 3) and motion-capture (Nintendo Wii) conditions. Violent video game play led to less aggression when participants used motion-capture controls. Study 2 eliminated potential confounds by using the only game on the Wii system that can be played identically with or without motion capture (Punch-Out!!). Again, participants who used motion-capture were less aggressive. Study 3 looked for effects of cooperative vs. competitive play during 2-player motion-capture gaming (Soul Calibur, Wii). Participants using motion-capture controls in competitive and cooperative scenarios did not differ from baseline. These results run counter to standard models relating violent video game play to aggressive behavior, highlighting the difficulty in anticipating the effects of newer, more immersive technology.     

基于工作流网的游戏作弊检测系统建模

近年来,游戏产业发展迅速。游戏不再局限于娱乐消遣,并且已经发展成为一种职业。与此同时,作弊技术对游戏产业的发展危害巨大,提出一种基于工作流网的作弊检测模型,用工作流网对作弊行为进行建模,利用流程树将工作流网转变为流程树,进而进行模型的融合,融合后的模型可以有效地识别一些作弊行为。