Subjective and behavioral presence measurement and interactivity in the collaborative augmented reality game TimeWarp

Presence is usually assessed via a variety of subjective and objective measures. However, constraints often result in subjective measurements using questionnaires as a key method of data collection. In this paper we present a study of 44 participants of a collaborative augmented reality game known as TimeWarp which used both subjective and objective behavioral measures. Behavior as coded from video recordings of one scene of the game and self-reports about feelings of presence were compared. Our findings indicate that pointing behavior and verbal responses to the virtual content are correlated negatively to sense of presence. We further investigated the influence of subjectively perceived interactivity on perceived presence. We found that the interaction possibilities perceived by the participants predicted their experience of social presence with the virtual characters in the game. Furthermore, playing together with another person did not result in decreased social presence of the virtual characters. Implications for presence research are discussed.     

Autonomous agents and human cultures in the trust–revenge game

Autonomous agents developed by experts are embedded with the capability to interact well with people from different cultures. When designing expert agents intended to interact with autonomous agents developed by non-game theory agents (NGTE), it is beneficial to obtain insights on the behavior of these NGTE agents. Is the behavior of these NGTE agents similar to human behavior from different cultures? This is an important question as such a quality would allow an expert agent interacting with NGTE agents to model them using the same methods that are used to model humans from different cultures. To study this point, we evaluated NGTE agents behavior using a game called the Trust–Revenge game, which is known in social science for capturing different human tendencies. The Trust–Revenge game has a unique subgame-perfect equilibrium strategy profile, however, very rarely do people follow it. We compared the behavior of autonomous agents to the actions of several human demographic groups—one of which is similar to the designers of the autonomous agents. We claim that autonomous agents are similar to human players from various cultures. This enables the use of approaches, developed for handling cultural diversity among humans, to be applied for interaction with NGTE agents. This paper also analyzes additional aspects of autonomous agents behavior and whether composing autonomous agents affects human behavior.     

Implications of the ability to learn simple actions on the efficiency of the evolution of social behavior of agents

We investigate the effect of the ability to learn simple actions on the performance characteristics of the evolution of social behavior in agents situated in an inherently cooperative environment. Using a continuous predator–prey pursuit problem, we verified that relatively complex social behavior emerges from simple, implicit, locally defined, and thus robust and scalable interactions between the predator agents. Considering a distinct aspect of the phenomenon of emergence, we hypothesize that the ability of agents to learn how to perform simple, atomic acts of implicit interaction might facilitate the evolution of more complex behavior. The empirical results indicate that incorporation of the proposed approach to learning in genetic programming (employed as an algorithmic paradigm to evolve the social behavior of the agents) is associated with about a two-fold decrease in the computational effort of evolution.This work was presented, in part, at the 9th International Symposium on Artificial Life and Robotics, Oita, Japan, January 28–30, 2004     

Touch-Space: Mixed Reality Game Space Based on Ubiquitous, Tangible, and Social Computing

This paper presents a novel computer entertainment system which recaptures human touch and physical interaction with the real-world environment as essential elements of the game play, whilst also maintaining the exciting fantasy features of traditional computer entertainment. Our system called ‘Touch-Space’ is an embodied (ubiquitous, tangible, and social) computing based Mixed Reality (MR) game space which regains the physical and social aspects of traditional game play. In this novel game space, the real-world environment is an essential and intrinsic game element, and the human’s physical context influences the game play. It also provides the full spectrum of game interaction experience ranging from the real physical environment (human to human and human to physical world interaction), to augmented reality, to the virtual environment. It allows tangible interactions between players and virtual objects, and collaborations between players in different levels of reality. Thus, the system re-invigorates computer entertainment systems with social human-to-human and human-to-physical touch interactions. Correspondence to: Professor A. Cheok, National University of Singapore, 10 Kent Ridge Crescent, Singapore 119260. Email: adriancheok@nus.edu.sg     

社会感知计算:概念、问题及其研究进展

普适计算技术的发展极大地丰富和增强了人类获取数据的途径和能力,如何利用这些感知数据,理解人类的社会行为与活动,实现计算“以人为中心”并为社会服务的目标,是当前信息领域的重要问题.本文介绍了计算机科学领域的一个刚刚兴起的研究主题——社会感知计算.社会感知计算旨在通过人类生活空间日益部署的大规模多种类传感设备,实时感知识别社会个体的行为,分析挖掘群体社会交互特征和规律,辅助个体社会行为,支持社群的互动、沟通和协作.论文讨论了社会感知计算的概念、起源、模型和主要研究问题,综述了社会感知计算典型系统与应用、数据感知、行为与交互分析、社会理论与规律验证以及社会交互高效支持等方面的研究进展.     

Child–robot interaction across cultures: How does playing a game with a social robot compare to playing a game alone or with a friend?

The present study investigates how children from two different cultural backgrounds (Pakistani, Dutch) and two different age groups (8 and 12 year olds) experience interacting with a social robot (iCat) during collaborative game play. We propose a new method to evaluate children’s interaction with such a robot, by asking whether playing a game with a state-of-the-art social robot like the iCat is more similar to playing this game alone or with a friend. A combination of self-report scores, perception test results and behavioral analyses indicate that child–robot interaction in game playing situations is highly appreciated by children, although more by Pakistani and younger children than by Dutch and older children. Results also suggest that children enjoyed playing with the robot more than playing alone, but enjoyed playing with a friend even more. In a similar vein, we found that children were more expressive in their non-verbal behavior when playing with the robot than when they were playing alone, but less expressive than when playing with a friend. Our results not only stress the importance of using new benchmarks for evaluating child–robot interaction but also highlight the significance of cultural differences for the design of social robots.     

A cognitive-behavioral model of problematic online gaming in adolescents aged 12–22 years

The aim of this study was to apply the cognitive behavioral model of problematic Internet use to the context of online game use to obtain a better understanding of problematic use of online games and its negative consequences. In total, 597 online game playing adolescents aged 12–22 years participated in this study. Results showed that the cognitive behavioral model of problematic Internet use can also be used in the context of online game use. More specifically, preference for online social interaction, mood regulation and deficient self-regulation appeared to play an important role in predicting negative outcomes from problematic online game use. Together, these cognitions and behaviors explained 79% of the variance of negative outcomes scores. These findings can be used to develop strategies that aim at reducing problematic online game behavior and its negative consequences.     

Design for emergence: experiments with a mixed reality urban playground game

In this paper we present our work in the design of ubiquitous social experiences, aiming to foster group participation and spontaneous playful behaviours in a city environment. We outline our approach of design for emergence: to provide just enough of a game context and challenge for people to be creative, to extend and enrich the experience of play through their interaction in the real world. CitiTag is our mixed reality testbed, a wireless location-based multiplayer game based on the concept of playground ‘tag’. We describe the design and implementation of CitiTag and discuss results from two user studies.     

Do perceived use contexts influence usage behavior? An instrument development of perceived use context

In this study, we advance current knowledge on IS usage behavior by introducing the concepts of time, location, social, and technological use in perceived use context. We develop an instrument to verify the effects of use context on intention-to-use game services. We find that contextual factors of perceived use context (i.e., perceived time use, perceived location use, perceived social use, and perceived technological use) influence users’ behavioral beliefs (i.e., perceived usefulness and perceived ease of use), which leads to their subsequent attitude and behavioral intention toward using game services. Grounded in our findings, key implications for theory and practice are discussed.     

See-through techniques for referential awareness in collaborative virtual reality

Multi-user virtual reality systems enable natural collaboration in shared virtual worlds. Users can talk to each other, gesture and point into the virtual scenery as if it were real. As in reality, referring to objects by pointing results often in a situation whereon objects are occluded from the other users' viewpoints. While in reality this problem can only be solved by adapting the viewing position, specialized individual views of the shared virtual scene enable various other solutions. As one such solution we propose show-through techniques to make sure that the objects one is pointing to can always be seen by others. We first study the impact of such augmented viewing techniques on the spatial understanding of the scene, the rapidity of mutual information exchange as well as the proxemic behavior of users. To this end we conducted a user study in a co-located stereoscopic multi-user setup. Our study revealed advantages for show-through techniques in terms of comfort, user acceptance and compliance to social protocols while spatial understanding and mutual information exchange is retained. Motivated by these results we further analyze whether show-through techniques may also be beneficial in distributed virtual environments. We investigated a distributed setup for two users, each participant having its own display screen and a minimalist avatar representation for each participant. In such a configuration there is a lack of mutual awareness, which hinders the understanding of each other's pointing gestures and decreases the relevance of social protocols in terms of proxemic behavior. Nevertheless, we found that show-through techniques can improve collaborative interaction tasks even in such situations.     

Analyzing the Adequacy of Interaction Paradigms in Artificial Reality Experiences

In Artificial Reality experiences, that is, interactive, unencumbered, full-body, 2D vision-based virtual reality (VR) experiences (heirs of the seminal Videoplace by Myron Krueger), there are two possible interaction paradigms, namely, first-person and third-person—which differ significantly from the classic VR first- and third-person notions. Up until now, these two paradigms had not been compared or objectively analyzed in such systems. Moreover, most systems are based on the third-person paradigm without a specific justification, most probably due to the influence of the original Videoplace system and because it is the only paradigm available in commercial development tools and leisure systems. For example, many rehabilitation projects have chosen to use these VR systems because of their many advantages. However, most of these projects and research have blindly adopted the third-person paradigm. Hence, the field of virtual rehabilitation has analyzed the beneficial properties of these systems without considering the first-person paradigm that could potentially present better adequacy. To find and understand potential differences between the two paradigms, we have defined an application categorization from which we developed two full-body interactive games and set up an experiment to analyze each game in both paradigms. We studied how 39 participants played these games and we quantitatively and qualitatively analyzed how each paradigm influenced the experience, the activity and the behavior of the users and the efficiency in accomplishing the required goals. We present the results of these experiments and their general implications, and especially for virtual rehabilitation due to the potential impact these systems may have in the well-being of many people.     

Group interaction analysis in dynamic context.

Computer understanding of human actions and interactions is one of the key research issues in human computing. In this regard, context plays an essential role in semantic understanding of human behavioral and social signals from sensor data. This paper put forward an event-based dynamic context model to address the problems of context awareness in the analysis of group interaction scenarios. Event-driven multilevel dynamic Bayesian network is correspondingly proposed to detect multilevel events, which underlies the context awareness mechanism. Online analysis can be achieved, which is superior over previous works. Experiments in our smart meeting room demonstrate the effectiveness of our approach.     

Examining the Effectiveness of Gamification in Human Computation

Within the human computation paradigm, gamification is increasingly gaining interest. This is because an enjoyable experience generated by game features can be a powerful approach to attract participants. Although potentially useful, little research has been conducted into understanding the effectiveness of gamification in human computation. In this experimental study, we operationalized effectiveness as perceived engagement and user acceptance and examined it by comparing the performance of a gamified human computation system against a non-gamified version. We also investigate the determinants of acceptance and how their effects differ between these two systems. Analysis of our data found that participants experienced more engagement and showed higher behavioral intentions toward the gamified system. Moreover, perceived output quality and perceived engagement were significant determinants of acceptance of the gamified system. In contrast, determinants for acceptance of the non-gamified system were perceived output quality and perceived usability.     

严肃游戏中虚拟角色行为建模综述

严肃游戏是计算机游戏一个新的发展方向,可以提供形象互动的模拟教学环境,已经广泛应用于科学教育、康复医疗、应急管理、军事训练等领域。虚拟角色是严肃游戏中模拟具有生命特征的图形实体,行为可信的虚拟角色能够提升用户使用严肃游戏的体验感。严肃游戏中的图形渲染技术已经逐步成熟,而虚拟角色行为建模的研究尚在初级阶段。可信的虚拟角色必须能够具有感知、情绪和行为能力。本文分别从游戏剧情与行为、行为建模方法、行为学习和行为建模评价等4个方面来分析虚拟角色行为建模研究。分析了有限状态机和行为树的特点,讨论了虚拟角色的行为学习方法。指出了强化学习的关键要素,探讨了深度强化学习的应用途径。综合已有研究,归纳了虚拟角色行为框架,该框架主要包括感觉输入、知觉分析、行为决策和动作4大模块。从情感计算的融入、游戏剧情和场景设计、智能手机平台和多通道交互4个角度讨论需要进一步研究的问题。虚拟角色的行为建模需要综合地考虑游戏剧情、机器学习和人机交互技术,构建具有自主感知、情绪、行为、学习能力、多通道交互的虚拟角色能够极大地提升严肃游戏的感染力,更好地体现寓教于乐。     

Automatic analysis and identification of verbal aggression and abusive behaviors for online social games

Online multiplayer games create new social platforms, with their own etiquette, social rules of conduct and ways of expression. What counts as aggressive and abusing behavior may change depending on the platform, but most online gaming companies need to deal with aggressive and abusive players explicitly. This usually is tied to a reporting mechanism where the offended player reports an offense. In this paper, we develop tools for validating whether a verbal aggression offense report refers to a real offense or not, in the context of a very popular online social game, called Okey. Our approach relies on the analysis of player behavior and characteristics of offending players. In the proposed system, chat records and other social activities in the game are taken into account, as well as player history. This methodology is sufficiently generic, and it can be applied to similar gaming platforms, thus describing a useful tool for game companies. We report our results on data collected over a six months period, involving 100,000 users and 800,000 game records, and illustrate the viability of such analysis, while providing insights on the factors associated with verbal aggression and abusive behavior for social games.     

An interactive space that learns to influence human behavior

A key question in the design of intelligent environments is how a space can influence the actions of its users, and how such behavior can be learned. We present the results of experiments conducted as part of the Ada project, an interactive entertainment exhibit deployed at the Swiss national exhibition Expo.02. We used a learning model called distributed adaptive control (DAC) that is based on the animal learning paradigms of classical and operant conditioning. DAC has been developed using mobile robots in foraging tasks. Here, it was applied to the learning of effective cues for guiding visitors in a given direction. Our results show that, by using this learning mechanism, Ada was able to influence the behavior of visitors by learning to deploy particular types of cues. Many visitors could be induced to move toward a region of the space that they normally avoided visiting-an effect that can be seen as a spatial classification of visitors into interactive and noninteractive categories. In our analysis, we also introduce a measure of human activity that combines different types of data to capture key aspects of human behavior in interactive spaces.     

Reciprocity norms and information-sharing behavior in online consumption communities: An empirical investigation of antecedents and moderators

This study seeks a better understanding of information-sharing behavior in online consumption communities by investigating both the antecedents and moderating mechanisms of such behavior. Using self-reported data collected over two periods, along with objective behavioral data, the authors show that a reciprocity norm functions as a proximal determinant of information-sharing behavior. This norm also channels the effects of social, hedonic, and utilitarian community values on sharing behavior. The results reveal that the conversion of reciprocity norms into information-sharing behavior depends on individual and contextual conditions. These significant insights reflect the integration of consumer resource allocation theory with a reciprocity framework to establish an explanatory platform for members’ information-sharing behavior in online communities. Both theoretical and practical implications are discussed.     

基于ACP的动态网民群体运动组织建模与计算实验研究

由互联网促成的社会运动组织一经出现, 就受到了广大社会学者以及计算机领域专家的广泛关注. 一方面, 互联网特别是移动互联网在整合信息、引发共振、实时分享及高度互动等方面的特性, 为网民行为的大规模快速聚集提供了直通渠道, 使得多角度超视距观察并研究在线人群复杂行为及其组织特性成为可能; 另一方面, 这一研究在社会化媒体营销、共享经济、非军事组织行动中的应用意义愈加显著. 本文引入群体行为动力学和社会运动组织理论的研究, 提出基于ACP的动态网民群体运动组织(Cyber movement organizations, CMOs)研究方法. 本文工作首先使用多智能体建模方法构造双层结构的人工社区模型, 以此为基础对动态网民的个体以及群体动态组织行为展开计算实验探讨, 重点阐释了社区用户的交互行为机制及群体组织活动的建模机制, 为揭示微观个体简单行为对于宏观群体复杂涌现现象的影响奠定基础.