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A Survey on Story Generation Techniques for Authoring Computational Narratives 计算叙事的故事生成技术综述
Q2 Computer Science Pub Date : 2017-09-01 DOI: 10.1109/TCIAIG.2016.2546063
Ben A. Kybartas, Rafael Bidarra
Computers are often used as tools to design, implement, and even visualize a variety of narrative forms. Many researchers and artists are now further attempting to engage the computer actively throughout the development of the narrative itself. Any form of computational narrative authoring is at some level always mixed-initiative , meaning that the processing capabilities of the computer are utilized with a varying degree to automate certain features of the authoring process. We structure this survey by focusing on two key components of stories, plot and space, and more specifically the degree to which these are either automated by the computer or authored manually. By examining the successes of existing research, we identify potential new research directions in the field of computational narrative. We also identify the advantages of developing a standard model of narrative to allow for collaboration between plot and space automation techniques. This would likely benefit the field of automated space generation with the strengths in the field of automated plot generation.
计算机经常被用作设计、实现甚至可视化各种叙事形式的工具。许多研究人员和艺术家现在正进一步尝试在叙事本身的整个发展过程中积极参与计算机。任何形式的计算叙事创作在某种程度上都是混合主动的,这意味着计算机的处理能力在不同程度上被用来自动化创作过程的某些特征。我们通过关注故事的两个关键组成部分,情节和空间来构建这项调查,更具体地说,这些内容在多大程度上是由计算机自动化或手动编写的。通过考察现有研究的成功,我们确定了计算叙事领域潜在的新研究方向。我们还确定了开发标准叙事模型的优势,以允许情节和空间自动化技术之间的合作。这可能有利于自动空间生成领域,同时具有自动绘图领域的优势。
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引用次数: 100
Evolutionary Behavior Tree Approaches for Navigating Platform Games 导航平台游戏的进化行为树方法
Q2 Computer Science Pub Date : 2017-09-01 DOI: 10.1109/TCIAIG.2016.2543661
Miguel Nicolau, Diego Pérez-Liébana, M. O’Neill, A. Brabazon
Computer games are highly dynamic environments, where players are faced with a multitude of potentially unseen scenarios. In this paper, AI controllers are applied to the Mario AI benchmark platform, by using the grammatical evolution system to evolve behavior tree structures. These controllers are either evolved to both deal with navigation and reactiveness to elements of the game or used in conjunction with a dynamic A* approach. The results obtained highlight the applicability of behavior trees as representations for evolutionary computation and their flexibility for incorporation of diverse algorithms to deal with specific aspects of bot control in game environments.
电脑游戏是高度动态的环境,玩家面临着大量潜在的未知场景。本文将AI控制器应用于马里奥AI基准平台,利用语法进化系统进化行为树结构。这些控制器要么用来处理导航和对游戏元素的反应,要么与动态a *方法结合使用。所获得的结果突出了行为树作为进化计算表示的适用性,以及它们在处理游戏环境中bot控制的特定方面时结合各种算法的灵活性。
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引用次数: 56
Design and Evaluation of a Data-Driven Scenario Generation Framework for Game-Based Training 基于游戏训练的数据驱动场景生成框架的设计与评估
Q2 Computer Science Pub Date : 2017-09-01 DOI: 10.1109/TCIAIG.2016.2541168
Linbo Luo, Haiyan Yin, Wentong Cai, J. Zhong, M. Lees
Generating suitable game scenarios that can cater for individual players has become an emerging challenge in procedural content generation. In this paper, we propose a data-driven scenario generation framework for game-based training. An evolutionary scenario generation process is designed with a fitness evaluation methodology that integrates the processes of AI player modeling, simulation and model training based on artificial neural networks. The fitness function for scenario evaluation can be automatically constructed based on the proposed methodology. To further enhance the evaluation of scenarios, we specifically study the impact of the timing of events in a scenario and propose a generic scenario representation model that characterizes individual scenario based on the types and timing of events in the scenario. We present an extensive evaluation of our framework by validating our AI player model, demonstrating the impact of timing of events in a scenario and comparing the effectiveness of our data-driven framework with our previous heuristic-based approach and a random baseline. The results show that it is necessary to consider the timing of events for scenario evaluation and the proposed framework works well in generating scenarios for game-based training.
生成适合个人玩家的游戏场景已成为程序内容生成中的一个新兴挑战。在本文中,我们提出了一个用于基于游戏的训练的数据驱动场景生成框架。采用体能评估方法设计了一个进化场景生成过程,该方法集成了基于人工神经网络的人工智能玩家建模、模拟和模型训练过程。基于所提出的方法,可以自动构建场景评估的适应度函数。为了进一步加强对场景的评估,我们专门研究了场景中事件发生时间的影响,并提出了一个通用的场景表示模型,该模型基于场景中事件的类型和时间来表征单个场景。我们通过验证我们的人工智能玩家模型,展示场景中事件发生时间的影响,并将我们的数据驱动框架的有效性与我们以前基于启发式的方法和随机基线进行比较,对我们的框架进行了广泛的评估。结果表明,在场景评估中有必要考虑事件的时间安排,并且所提出的框架在生成基于游戏的训练场景方面效果良好。
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引用次数: 20
Understanding the Interplay of Model Complexity and Fidelity in Multiagent Systems via an Evolutionary Framework 通过进化框架理解多智能体系统中模型复杂性和保真度的相互作用
Q2 Computer Science Pub Date : 2017-09-01 DOI: 10.1109/TCIAIG.2016.2560882
E. Lakshika, M. Barlow, A. Easton
Modern video games come with highly realistic graphics enabling the players to interact with visually rich virtual worlds. Realistic (life-like) animation of nonplayer characters (NPCs) in such virtual worlds is particularly important to enhance the gaming experience. Multiagent systems are one effective approach to synthesize life-like behaviors and interactions by codifying simple rules into NPCs (each NPC as an autonomous agent). However, such behaviors generally come at the cost of increasing computational expense and complexity in terms of aspects such as number of rules and parameters. Therefore, the desire for high fidelity (highly realistic) behaviors is often in conflict with the drive for low complexity. Multiobjective evolutionary algorithms provide a sophisticated mechanism to optimize two or more conflicting objectives simultaneously. However, evolutionary computing techniques need an appropriate objective function to drive the exploration in the correct direction. Pairing of evolutionary techniques and multiagent systems is challenging in the classes of problems in which the fitness is evaluated based on human aesthetic judgment rather than on objective forms of measurements. In this study, we present a multiobjective evolutionary framework to evolve low complexity and high fidelity multiagent systems by utilizing a machine learning system trained by bootstrapping human aesthetic judgment. We have gathered empirical data in three problem areas—simulation of conversational group dynamics, sheepdog herding behaviors, and traffic dynamics, and show the effectiveness of our approach in deriving low complexity and high fidelity multiagent systems. Further, we have identified common properties of the Pareto-optimal frontiers in the three problem areas that can ultimately lead to an understanding of a relationship between simulation model complexity and behavior fidelity. This understanding will be useful in deciding which level of behavioral fidelity is required for the characters in video games based on the distance to the camera, importance to the scene, and available computational resources.
现代电子游戏具有高度逼真的图形,使玩家能够与视觉丰富的虚拟世界进行互动。在这样的虚拟世界中,非玩家角色(npc)的逼真动画对于增强游戏体验尤为重要。多代理系统是通过将简单规则编入NPC(每个NPC都是自主代理)来合成逼真行为和交互的有效方法。然而,这样的行为通常是以增加计算费用和复杂性为代价的,比如规则和参数的数量。因此,对高保真度(高度逼真)行为的渴望常常与对低复杂性的追求相冲突。多目标进化算法提供了一种复杂的机制来同时优化两个或多个相互冲突的目标。然而,进化计算技术需要一个合适的目标函数来推动探索朝着正确的方向发展。在基于人类审美判断而不是客观测量形式来评估适应度的问题中,将进化技术和多智能体系统配对是具有挑战性的。在这项研究中,我们提出了一个多目标进化框架,通过利用自引导人类审美判断训练的机器学习系统来进化低复杂性和高保真度的多智能体系统。我们收集了三个问题领域的经验数据——会话群体动力学模拟、牧羊犬放牧行为和交通动力学,并展示了我们的方法在推导低复杂性和高保真度的多智能体系统方面的有效性。此外,我们已经确定了三个问题领域中帕累托最优边界的共同属性,这些属性最终可以导致对仿真模型复杂性和行为保真度之间关系的理解。这种理解将有助于根据与摄像机的距离、对场景的重要性和可用的计算资源来决定电子游戏中角色所需的行为保真度水平。
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引用次数: 13
A User Trust System for Online Games—Part I: An Activity Theory Approach for Trust Representation 网络游戏用户信任系统——第一部分:信任表征的活动理论方法
Q2 Computer Science Pub Date : 2017-09-01 DOI: 10.1109/TCIAIG.2016.2592965
R. Cardoso, A. Gomes, M. Freire
In virtual worlds (including computer games), users develop trust relationships from their in-world interactions with others. However, these trust relationships end up not being represented in the data structures (or databases) of such virtual worlds, though they sometimes appear associated with reputation and recommendation systems. In addition, as far as we know, the user is not provided with a personal trust tool to sustain his/her decision-making while he/she interacts with other users in the virtual or game world. In order to come up with a computational formal representation of these personal trust relationships, we need to succeed in converting in-world interactions into reliable sources of trust-related data. In this paper, we develop the required formalisms to gather and represent in-world interactions—which are based on the activity theory—as well as a method to convert in-world interactions into trust networks. In the companion paper, we use these trust networks to produce a computational trust decision based on subjective logic. This solution aims at supporting in-world user (or avatar) decisions about others in the game world.
在虚拟世界(包括电脑游戏)中,用户通过与他人的互动建立信任关系。然而,这些信任关系最终没有在这种虚拟世界的数据结构(或数据库)中表示出来,尽管它们有时与声誉和推荐系统相关联。此外,据我们所知,当用户在虚拟或游戏世界中与其他用户互动时,并没有提供一个个人信任工具来支持他/她的决策。为了提出这些个人信任关系的计算形式表示,我们需要成功地将现实世界中的交互转换为可靠的信任相关数据来源。在本文中,我们基于活动理论开发了收集和表示虚拟世界交互所需的形式化方法,以及将虚拟世界交互转换为信任网络的方法。在本文中,我们使用这些信任网络来产生基于主观逻辑的计算信任决策。这个解决方案旨在支持游戏世界中的用户(或角色)对游戏世界中其他人的决定。
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引用次数: 5
Ahura: A Heuristic-Based Racer for the Open Racing Car Simulator Ahura:开放赛车模拟器的启发式赛车手
Q2 Computer Science Pub Date : 2017-09-01 DOI: 10.1109/TCIAIG.2016.2565661
M. Bonyadi, Z. Michalewicz, Samadhi Nallaperuma, F. Neumann
Designing automatic drivers for car racing is an active field of research in the area of robotics and artificial intelligence. A controller called Ahura (a heuristic-based racer) for the open racing car simulator is proposed in this paper. Ahura includes five modules, namely steer controller, speed controller, opponent manager, dynamic adjuster, and stuck handler. These modules have 23 parameters all together that are tuned using an evolutionary strategy for a particular car to ensure fast and safe drive on different tracks. These tuned parameters are further modified by the dynamic adjuster module during the run according to the width, friction, and dangerous zones of the track. The dynamic adjustment enables Ahura to decide on-the-fly based on the current situation; hence, it eliminates the need for prior knowledge about the characteristics of the track. The driving performance of Ahura is compared with other state-of-the-art controllers on 40 tracks when they drive identical cars. Our experiments indicate that Ahura performs significantly better than other controllers in terms of damage and completion time especially on complex tracks (road tracks). Also, experiments show that the overtaking strategy of Ahura is safer and more effective compared to other controllers.
为赛车设计自动驾驶是机器人和人工智能领域的一个活跃研究领域。提出了一种用于开放式赛车模拟器的启发式控制器Ahura (heuristic-based racer)。Ahura包括五个模块,即转向控制器、速度控制器、对手管理器、动态调节器和卡住处理程序。这些模块共有23个参数,使用进化策略对特定汽车进行调整,以确保在不同轨道上快速安全行驶。在运行过程中,动态调整模块根据赛道的宽度、摩擦力和危险区域进一步修改这些调整后的参数。动态调整使Ahura能够根据当前情况动态决定;因此,它消除了对轨道特性的先验知识的需要。Ahura的驾驶性能与其他最先进的控制器在40条轨道上驾驶相同的汽车时进行比较。我们的实验表明,在损坏和完成时间方面,Ahura明显优于其他控制器,特别是在复杂的轨道(公路轨道)上。实验表明,Ahura的超车策略比其他控制器更安全有效。
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引用次数: 7
Review of the Use of AI Techniques in Serious Games: Decision Making and Machine Learning 回顾AI技术在严肃游戏中的应用:决策制定和机器学习
Q2 Computer Science Pub Date : 2017-06-01 DOI: 10.1109/TCIAIG.2015.2512592
Maite Frutos-Pascual, Begonya Garcia Zapirain
The video game market has become an established and ever-growing global industry. The health of the video and computer games industry, together with the variety of genres and technologies available, means that video game concepts and programmes are being applied in numerous different disciplines. One of these is the field known as serious games. The main goal of this paper is to collect all the relevant articles published during the last decade and create a trend analysis about the use of certain artificial intelligence algorithms related to decision making and learning in the field of serious games. A categorization framework was designed and outlined to classify the 129 papers that met the inclusion criteria. The authors made use of this categorization framework for drawing some conclusions regarding the actual use of intelligent serious games. The authors consider that over recent years enough knowledge has been gathered to create new intelligent serious games to consider not only the final aim but also the technologies and techniques used to provide players with a nearly real experience. However, researchers may need to improve their testing methodology for developed serious games, so as to ensure they meet their final purposes.
电子游戏市场已经成为一个成熟且不断发展的全球性产业。电子游戏和电脑游戏产业的健康发展,加上游戏类型和技术的多样性,意味着电子游戏的概念和程序正被应用于许多不同的学科。其中之一就是严肃游戏领域。本文的主要目标是收集过去十年中发表的所有相关文章,并创建一个关于在严肃游戏领域中使用与决策和学习相关的某些人工智能算法的趋势分析。设计并概述了分类框架,对符合纳入标准的129篇论文进行分类。作者利用这一分类框架得出了一些关于智能严肃游戏实际使用的结论。作者认为,近年来已经收集了足够的知识来创造新的智能严肃游戏,不仅要考虑最终目标,还要考虑为玩家提供近乎真实的体验所使用的技术和技巧。然而,研究人员可能需要改进他们开发的严肃游戏的测试方法,以确保它们达到最终目的。
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引用次数: 33
A Model-Based Approach to Optimizing Ms. Pac-Man Game Strategies in Real Time 一种基于模型的实时优化吃豆人游戏策略的方法
Q2 Computer Science Pub Date : 2017-06-01 DOI: 10.1109/TCIAIG.2016.2523508
Greg Foderaro, Ashleigh Swingler, S. Ferrari
This paper presents a model-based approach for computing real-time optimal decision strategies in the pursuit-evasion game of Ms. Pac-Man. The game of Ms. Pac-Man is an excellent benchmark problem of pursuit-evasion game with multiple, active adversaries that adapt their pursuit policies based on Ms. Pac-Man’s state and decisions. In addition to evading the adversaries, the agent must pursue multiple fixed and moving targets in an obstacle-populated environment. This paper presents a novel approach by which a decision-tree representation of all possible strategies is derived from the maze geometry and the dynamic equations of the adversaries or ghosts. The proposed models of ghost dynamics and decisions are validated through extensive numerical simulations. During the game, the decision tree is updated and used to determine optimal strategies in real time based on state estimates and game predictions obtained iteratively over time. The results show that the artificial player obtained by this approach is able to achieve high game scores, and to handle high game levels in which the characters speeds and maze complexity become challenging even for human players.
本文提出了一种基于模型的“吃豆女士”追逃博弈实时最优决策策略计算方法。《吃豆人女士》是一款优秀的追逃基准问题游戏,它拥有多个活跃的对手,这些对手会根据吃豆人女士的状态和决定调整自己的追逃策略。除了躲避对手之外,代理还必须在一个充满障碍物的环境中追捕多个固定和移动的目标。本文提出了一种新的方法,该方法从迷宫的几何形状和对手或幽灵的动态方程中推导出所有可能策略的决策树表示。通过大量的数值模拟验证了所提出的鬼动力和决策模型。在博弈过程中,决策树被更新,并用于根据状态估计和博弈预测实时确定最优策略。结果表明,通过这种方法获得的人工玩家能够获得较高的游戏分数,并且能够处理角色速度和迷宫复杂性甚至对人类玩家都具有挑战性的高游戏关卡。
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引用次数: 10
Product Propagation: A Backup Rule Better Than Minimaxing? 产品传播:比最小化更好的备份规则?
Q2 Computer Science Pub Date : 2017-06-01 DOI: 10.1109/TCIAIG.2015.2508966
H. Kaindl, H. Horacek, A. Scheucher
There is a gap between theory and practice regarding the assessment of minimaxing versus product propagation. The use of minimaxing in real programs for certain two-player games like chess is more or less ubiquitous, due to the substantial search space reductions enabled by several pruning algorithms. In stark contrast, some theoretical work supported the view that product propagation could be a viable alternative, or even superior on theoretical grounds. In fact, these rules have different conceptual problems. While minimaxing treats heuristic values as true values, product propagation interprets them as independent probabilities. So, which is the better rule for backing up heuristic values in game trees, and under which circumstances? We present a systematic analysis and results of simulation studies that compare these backup rules in synthetic trees with properties found in certain real game trees, for a variety of situations with characteristic properties. Our results show yet unobserved complementary strengths in their respective capabilities, depending on the size of node score changes (“quiet” versus “nonquiet” positions), and on the degree of advantage of any player over the opponent. In particular, exhaustive analyses for shallow depths show that product propagation can indeed be better than minimaxing when both approaches search to the same depth, especially for making decisions from a huge amount of alternatives, where deep searches are still prohibitive. However, our results also provide some justification for the more or less ubiquitous use of minimaxing in chess programs, where deep searches prevail and the pruning algorithms available for minimaxing make the difference.
关于最小化与产品传播的评估,理论与实践之间存在差距。在某些双人游戏(如国际象棋)的真实程序中,由于几种修剪算法能够大幅减少搜索空间,因此最小化的使用或多或少是普遍存在的。与此形成鲜明对比的是,一些理论工作支持这样一种观点,即产品传播可能是一种可行的替代方案,甚至在理论上更为优越。事实上,这些规则有不同的概念问题。当最小化将启发式值视为真值时,产品传播将其解释为独立的概率。那么,在游戏树中备份启发式值的最佳规则是什么?在什么情况下?我们提出了一个系统的分析和模拟研究结果,将合成树中的这些备份规则与某些真实游戏树中的属性进行了比较,适用于具有特征属性的各种情况。我们的研究结果显示,根据节点得分变化的大小(“安静”与“非安静”位置),以及任何球员相对于对手的优势程度,他们各自的能力存在尚未观察到的互补优势。特别是,对浅层深度的详尽分析表明,当两种方法都搜索到相同的深度时,产品传播确实比最小化要好,尤其是在从大量备选方案中做出决策时,深度搜索仍然令人望而却步。然而,我们的结果也为国际象棋程序中或多或少普遍使用的最小化提供了一些理由,在国际象棋程序,深度搜索占主导地位,而可用于最小化的修剪算法起到了作用。
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引用次数: 3
The ANGELINA Videogame Design System—Part I 安吉丽娜电子游戏设计系统——上
Q2 Computer Science Pub Date : 2017-06-01 DOI: 10.1109/TCIAIG.2016.2520256
Michael Cook, S. Colton, J. Gow
Automatically generating content for videogames has long been a staple of game development and the focus of much successful research. Such forays into content generation usually concern themselves with producing a specific game component, such as a level design. This has proven a rich and challenging area of research, but in focusing on creating separate parts of a larger game, we miss out on the most challenging and interesting aspects of game development. By expanding our scope to the automated design of entire games, we can investigate the relationship between the different creative tasks undertaken in game development, tackle the higher level creative challenges of game design, and ultimately build systems capable of much greater novelty, surprise, and quality in their output. This paper, the first in a series of two, describes two case studies in automating game design, proposing cooperative coevolution as a useful technique to use within systems that automate this process. We show how this technique allows essentially separate content generators to produce content that complements each other. We also describe systems that have used this to design games with subtle emergent effects. After introducing the technique and its technical basis in this paper, in the second paper in the series we discuss higher level issues in automated game design, such as potential overlap with computational creativity and the issue of evaluation.
自动生成视频游戏内容一直是游戏开发的主要内容,也是许多成功研究的焦点。这种对内容生成的尝试通常涉及制作特定的游戏组件,例如关卡设计。事实证明,这是一个丰富而富有挑战性的研究领域,但在专注于创建更大游戏的独立部分时,我们错过了游戏开发中最具挑战性和最有趣的方面。通过将我们的范围扩大到整个游戏的自动化设计,我们可以调查游戏开发中不同创意任务之间的关系,应对游戏设计中更高级别的创意挑战,并最终构建出能够在输出中获得更大新颖性、惊喜性和质量的系统。本文是两篇系列文章中的第一篇,描述了游戏设计自动化的两个案例研究,提出合作协同进化是一种有用的技术,可以在自动化这一过程的系统中使用。我们展示了这种技术如何允许本质上独立的内容生成器生成相互补充的内容。我们还描述了使用这种方法设计具有微妙突发效果的游戏的系统。在本文中介绍了该技术及其技术基础后,在本系列的第二篇论文中,我们讨论了自动化游戏设计中更高级别的问题,例如与计算创造力的潜在重叠和评估问题。
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引用次数: 52
期刊
IEEE Transactions on Computational Intelligence and AI in Games
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