Doing Virtually Nothing: Awareness and Accountability in Massively Multiplayer Online Worlds

To date the most popular and sophisticated types of virtual worlds can be found in the area of video gaming, especially in the genre of Massively Multiplayer Online Role Playing Games (MMORPG). Game developers have made great strides in achieving game worlds that look and feel increasingly realistic. However, despite these achievements in the visual realism of virtual game worlds, they are much less sophisticated when it comes to modeling face-to-face interaction. In face-to-face, ordinary social activities are “accountable,” that is, people use a variety of kinds of observational information about what others are doing in order to make sense of others’ actions and to tightly coordinate their own actions with others. Such information includes: (1) the real-time unfolding of turns-at-talk; (2) the observability of embodied activities; and (3) the direction of eye gaze for the purpose of gesturing. But despite the fact that today’s games provide virtual bodies, or “avatars,” for players to control, these avatars display much less information about players’ current state than real bodies do. In this paper, we discuss the impact of the lack of each type of information on players’ ability to tightly coordinate their activities and offer guidelines for improving coordination and, ultimately, the players’ social experience. “They come here to talk turkey with suits from around the world, and they consider it just as good as a face-to-face. They more or less ignore what is being said—a lot gets lost in translation, after all. They pay attention to the facial expressions and body language of the people they are talking to. And that’s how they know what’s going on inside a person’s head—by condensing fact from the vapor of nuance.” —Neal Stephenson, Snow Crash, 1992     

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     

User-Sensitive Inclusive Design

Although “User-Centred”, “Participatory”, and other similar design approaches have proved to be very valuable for mainstream design, their principles are more difficult to apply successfully when the user group contains, or is composed of, older and/or disabled users. In the field of design for older and disabled people, the “Universal Design”, “Inclusive Design” and “Design for All” movements have encouraged designers to extend their design briefs to include older and disabled people. The downside of these approaches is that they can tend to encourage designers to follow a traditional design path to produce a prototype design, and only then investigate how to modify their interfaces and systems to cope with older and/or disabled users. This can lead to an inefficient design process and sometimes an inappropriate design, which may be “accessible” to people with disabilities, but in practice unusable. This paper reviews the concept that the authors have called “User-Sensitive Inclusive Design”, which suggests a different approach to designing for marginalised groups of people. Rather than suggesting that designers rely on standards and guidelines, it is suggested that designers need to develop a real empathy with their user groups. A number of ways to achieve this are recommended, including the use of ethnography and techniques derived from professional theatre both for requirements gathering and for improving designers’ empathy for marginalised groups of users, such as older and disabled people.     

Dynamic Bayesian approach for detecting cheats in multi-player online games

Massively multi-player games hold a huge market in the digital entertainment industry. Companies invest heavily in game developments since a successful online game can attract millions of users, and this translates to a huge investment payoff. However, multi-player online games are also subjected to various forms of “hacks” and “cheats”. Hackers can alter the graphic rendering to reveal information otherwise be hidden in a normal game, or cheaters can use software robots to play the game automatically and thus gain an unfair advantage. To overcome these problems, some popular online games release software patches constantly to block “known” hacks or incorporate anti-cheating software to detect “known” cheats. This not only creates deployment difficulty but new cheats will still be able to breach the normal game logic until software patches or updates of the anti-cheating software are available. Moreover, the anti-cheating software themselves are also vulnerable to hacks. In this paper, we propose a “scalable” and “efficient” method to detect whether a player is cheating or not. The methodology is based on the dynamic Bayesian network approach. The detection framework relies solely on the game states and runs in the game server only. Therefore, it is invulnerable to hacks and it is a much more deployable solution. To demonstrate the effectiveness of the proposed method, we have implemented a prototype multi-player game system to detect whether a player is using any “aiming robot” for cheating or not. Experiments show that the proposed method can effectively detect cheaters on a first-person shooter game with extremely low false positive rate. We believe the proposed methodology and the prototype system provide a first step toward a systematic study of cheating detection and security research in the area of online multi-player games.     

A user-adaptive city guide system with an unobtrusive navigation interface

In this paper, we describe an intelligent location-aware city guide system, which adapts to each user’s preferences, and uses an intuitive “metal detector” interface for navigation. Our system analyzes each user’s past location data history to estimate individual preferences, and allows users to find shops that match their tastes in the same way a metal detector would be used to detect metal objects. The procedure with which the system picks out shops that match each user’s preferences includes a newly developed place learning algorithm, which can efficiently find frequented places, complete with their proper names (e.g. “The Ueno Royal Museum”). We have conducted a series of evaluation tests at a popular shopping district inside Tokyo, and the results validate the effectiveness of our overall approach.     

Opinion helpfulness prediction in the presence of “words of few mouths”

This paper identifies a widely existing phenomenon in social media content, which we call the “words of few mouths” phenomenon. This phenomenon challenges the development of recommender systems based on users’ online opinions by presenting additional sources of uncertainty. In the context of predicting the “helpfulness” of a review document based on users’ online votes on other reviews (where a user’s vote on a review is either HELPFUL or UNHELPFUL), the “words of few mouths” phenomenon corresponds to the case where a large fraction of the reviews are each voted only by very few users. Focusing on the “review helpfulness prediction” problem, we illustrate the challenges associated with the “words of few mouths” phenomenon in the training of a review helpfulness predictor. We advocate probabilistic approaches for recommender system development in the presence of “words of few mouths”. More concretely, we propose a probabilistic metric as the training target for conventional machine learning based predictors. Our empirical study using Support Vector Regression (SVR) augmented with the proposed probability metric demonstrates advantages of incorporating probabilistic methods in the training of the predictors. In addition to this “partially probabilistic” approach, we also develop a logistic regression based probabilistic model and correspondingly a learning algorithm for review helpfulness prediction. We demonstrate experimentally the superior performance of the logistic regression method over SVR, the prior art in review helpfulness prediction.     

Incremental learning of gestures for human–robot interaction

For a robot to cohabit with people, it should be able to learn people’s nonverbal social behavior from experience. In this paper, we propose a novel machine learning method for recognizing gestures used in interaction and communication. Our method enables robots to learn gestures incrementally during human–robot interaction in an unsupervised manner. It allows the user to leave the number and types of gestures undefined prior to the learning. The proposed method (HB-SOINN) is based on a self-organizing incremental neural network and the hidden Markov model. We have added an interactive learning mechanism to HB-SOINN to prevent a single cluster from running into a failure as a result of polysemy of being assigned more than one meaning. For example, a sentence: “Keep on going left slowly” has three meanings such as, “Keep on (1)”, “going left (2)”, “slowly (3)”. We experimentally tested the clustering performance of the proposed method against data obtained from measuring gestures using a motion capture device. The results show that the classification performance of HB-SOINN exceeds that of conventional clustering approaches. In addition, we have found that the interactive learning function improves the learning performance of HB-SOINN.     

User Environments and Individuals: Experience with Adaptive Interface Agents

The traditional style of working with computers generally revolves around the computer being used as a tool, with individual users directly initiating operations and waiting for the results of them. A more recent paradigm of human-computer interaction, based on the indirect management of computing resources, is agent-based interaction. The idea of delegation plays a key part in this approach to computer-based work, which allows individuals to relinquish the routine, mechanistic parts of their everyday tasks, having them performed automatically instead. Adaptive interfaces combine elements of both these approaches, where the goal is to have the interface adapt to its users rather than the reverse. This paper addresses some of the issues arising from a practical software development process which aimed to support individuals using this style of interaction. This paper documents the development of a set of classes which implement an architecture for adaptive interfaces. These classes are intended to be used as part of larger user interface systems which are to exhibit adaptive behaviour. One approach to the implementation of an adaptive interface is to use a set of software “agents”– simple processes which effectively run “in the background”– to decompose the task of implementing the interface. These agents form part of a larger adaptive interface architecture, which in turn forms a component of the adaptive system.     

Improving behavior of computer game bots using fictitious play

In modern computer games, "bots" - intelligent realistic agents play a prominent role in the popularity of a game in the market. Typically, bots are modeled using finite-state machine and then programmed via simple conditional statements which are hard-coded in bots logic. Since these bots have become quite predictable to an experienced games player, a player might lose interest in the game. We propose the use of a game theoretic based learning rule called fictitious play for improving behavior of these computer game bots which will make them less predictable and hence, more a enjoyable game.     

User interfaces for communication bridges across the digital divide

Connecting people across the “digital divide” is as much a social effort as a technological one. We are developing a community-centred approach to learn how interaction techniques can compensate for poor communication across the digital divide. We have incorporated the lessons learned regarding social intelligence design in an abstraction and in a device called the SoftBridge. The SoftBridge allows communication to flow from endpoints through adapters, getting converted if necessary, and out to destination endpoints. Field trials are underway with two communities in South Africa: disadvantaged Deaf users and an isolated rural community. Initial lessons learned show that we have to design user interfaces that allow users to understand and cope with delay. We also learned that social concerns are often more important than the technical issues in designing such systems.     

Move to get moved: a search for methods,tools and knowledge to design for expressive and rich movement-based interaction

The world is inherently meaningful for us, i.e. we perceive the world in terms of what we can do with it, and by physically interacting with it we access this meaning and express the meaning. We believe that this is the core reason and foundation for turning to movement-based interaction. ‘Interaction creates meaning’ does not only hold for users during interaction but also for designers when generating ideas and developing concepts. Therefore, we postulate that if one truly likes to design for movement-based interaction, one has to be or become an expert in movement, not just theoretically, by imagination or on paper, but by doing and experiencing while designing. In order to do so, we believe that designers need design tools, techniques, knowledge, awareness and skills that support their search for expressive, rich behaviour. Our search for this support resulted in several methods, tools and knowledge that help designers exploring, visualising and reflecting on interactions. Our developed methods and tools such as the Design Movement approach with its choreography of interaction, gestural design tools, interactive installations and interactive tangible sketching, have not only supported and inspired designers to design for movement-based interaction, but also resulted in surprising, fresh designs in comparison with the limited scope of rather uniform and traditional electronic consumer products. This paper discusses the possibilities and limitations of our approach.     

Cobot in LambdaMOO: An Adaptive Social Statistics Agent

We describe our development of Cobot, a novel software agent who lives in LambdaMOO, a popular virtual world frequented by hundreds of users. Cobot’s goal was to become an actual part of that community. Here, we present a detailed discussion of the functionality that made him one of the objects most frequently interacted with in LambdaMOO, human or artificial. Cobot’s fundamental power is that he has the ability to collect social statistics summarizing the quantity and quality of interpersonal interactions. Initially, Cobot acted as little more than a reporter of this information; however, as he collected more and more data, he was able to use these statistics as models that allowed him to modify his own behavior. In particular, cobot is able to use this data to “self-program,” learning the proper way to respond to the actions of individual users, by observing how others interact with one another. Further, Cobot uses reinforcement learning to proactively take action in this complex social environment, and adapts his behavior based on multiple sources of human reward. Cobot represents a unique experiment in building adaptive agents who must live in and navigate social spaces.     

Supporting casual interactions between board games on public tabletop displays and mobile devices

As more interactive surfaces enter public life, casual interactions from passersby are bound to increase. Most of these users can be expected to carry a mobile phone or PDA, which nowadays offers significant computing capabilities of its own. This offers new possibilities for interaction between these users’ private displays and large public ones. In this paper, we present a system that supports such casual interactions. We first explore a method to track mobile phones that are placed on a horizontal interactive surface by examining the shadows which are cast on the surface. This approach detects the presence of a mobile device, as opposed to any other opaque object, through the signal strength emitted by the built-in Bluetooth transceiver without requiring any modifications to the devices’ software or hardware. We then go on to investigate interaction between a Sudoku game running in parallel on the public display and on mobile devices carried by passing users. Mobile users can join a running game by placing their devices on a designated area. The only requirement is that the device is in discoverable Bluetooth mode. After a specific device has been recognized, a client software is sent to the device which then enables the user to interact with the running game. Finally, we explore the results of a study which we conducted to determine the effectiveness and intrusiveness of interactions between users on the tabletop and users with mobile devices.     

“Those found responsible have been sacked”: some observations on the usefulness of error

Erik Hollnagel’s body of work in the past three decades has molded much of the current research approach to system safety, particularly notions of “error”. Hollnagel regards “error” as a dead-end and avoids using the term. This position is consistent with Rasmussen’s claim that there is no scientifically stable category of human performance that can be described as “error”. While this systems view is undoubtedly correct, “error” persists. Organizations, especially formal business, political, and regulatory structures, use “error” as if it were a stable category of human performance. They apply the term to performances associated with undesired outcomes, tabulate occurrences of “error”, and justify control and sanctions through “error”. Although a compelling argument can be made for Hollnagel’s view, it is clear that notions of “error” are socially and organizationally productive. The persistence of “error” in management and regulatory circles reflects its value as a means for social control.     

Design-in-play: improving the variability of indoor pervasive games

Treasure is a pervasive game playing in the context of people’s daily living environments. Unlike previous pervasive games that are based on the predefined contents and proprietary devices, Treasure exploits the “design-in-play” concept to enhance the variability of a game in mixed-reality environments. Dynamic and personalized role design and allocation by players is enabled by exploring local smart objects as game props. The variability of the game is also enhanced by several other aspects, such as user-oriented context-aware action setting and playing environment redeployment. The effectiveness of the “design-in-play” concept is validated through a user study, where 15 subjects were recruited to play and author the trial game.     

SpaceGlue: linking spaces for adaptive service location

We describe a mechanism called SpaceGlue for adaptively locating services based on the preferences and locations of users in a distributed and dynamic network environment. In SpaceGlue, services are bound to physical locations, and a mobile user accesses local services depending on the current space he/she is visiting. SpaceGlue dynamically identifies the relationships between different spaces and links or “glues” spaces together depending on how previous users moved among them and used those services. Once spaces have been glued, users receive a recommendation of remote services (i.e., services provided in a remote space) reflecting the preferences of the crowd of users visiting the area. The strengths of bonds are implicitly evaluated by users and adjusted by the system on the basis of their evaluation. SpaceGlue is an alternative to existing schemes such as data mining and recommendation systems and it is suitable for distributed and dynamic environments. The bonding algorithm for SpaceGlue incrementally computes the relationships or “bonds” between different spaces in a distributed way. We implemented SpaceGlue using a distributed network application platform Ja-Net and evaluated it by simulation to show that it adaptively locates services reflecting trends in user preferences. By using “Mutual Information (MI)” and “F-measure” as measures to indicate the level of such trends and the accuracy of service recommendation, the simulation results showed that (1) in SpaceGlue, the F-measure increases depending on the level of MI (i.e., the more significant the trends, the greater the F-measure values), (2) SpaceGlue achives better precision and F-measure than “Flooding case (i.e., every service information is broadcast to everybody)” and “No glue case” by narrowing appropriate partners to send recommendations based on bonds, and (3) SpaceGlue achieves better F-measure with large number of spaces and users than other cases (i.e., “flooding” and “no glue”). Tomoko Itao is an alumna of NTT Network Innovation Laboratories     

Entertainment capture through heart rate activity in physical interactive playgrounds

An approach for capturing and modeling individual entertainment (“fun”) preferences is applied to users of the innovative Playware playground, an interactive physical playground inspired by computer games, in this study. The goal is to construct, using representative statistics computed from children’s physiological signals, an estimator of the degree to which games provided by the playground engage the players. For this purpose children’s heart rate (HR) signals, and their expressed preferences of how much “fun” particular game variants are, are obtained from experiments using games implemented on the Playware playground. A comprehensive statistical analysis shows that children’s reported entertainment preferences correlate well with specific features of the HR signal. Neuro-evolution techniques combined with feature set selection methods permit the construction of user models that predict reported entertainment preferences given HR features. These models are expressed as artificial neural networks and are demonstrated and evaluated on two Playware games and two control tasks requiring physical activity. The best network is able to correctly match expressed preferences in 64% of cases on previously unseen data (p−value 6 · 10⁻⁵). The generality of the methodology, its limitations, its usability as a real-time feedback mechanism for entertainment augmentation and as a validation tool are discussed.     

The gain and pain in taking the pilot seat: learning dynamics in a non immersive virtual solar system

This study describes and analyzes the learning interactions of nine high-school students’ free exploration of a virtual solar system (VSS). The VSS is a non-immersive three dimensional virtual environment based on real NASA planetary images. The computer screen serves as a “spacecraft’s window” for the learner to “fly” between objects, to change the system’s frame of reference and its pace. A systematic analysis of participants’ real-time observable interactions together with what they said revealed that each of them created an unique learning pattern within at least five different dimensions: (1) the cognitive dimension, (2) the affective dimension, (3) the navigation dimension, (4) the interface dimension, and (5) the assistance seeking dimension. The construction of meaning emerged as a non-linear process, which includes transitions between and within these dimensions. Three different styles of learning interactions were identified, suggesting that individual differences might be enhanced due to the unique VSS’ features. Overall, the VSS served as an enriching and motivational learning experience. The design of additional navigation tools and content scaffolding might help participants’ in building a sustained deep scientific understanding.     

Enhancing social communication of children with high-functioning autism through a co-located interface

This study evaluated the effectiveness of a 3-week intervention in which a co-located cooperation enforcing interface, called StoryTable, was used to facilitate collaboration and positive social interaction for six children, aged 8–10 years, with autistic spectrum disorder (ASD). The intervention focused on exposing pairs of children to an enforced collaboration paradigm while they narrated a story. Pre- and post-intervention tasks included a “low technology” version of the storytelling device and a non storytelling play situation using a free construction game. The outcome measure was a structured observation scale of social interaction. Results demonstrated progress in three areas of social behaviors. First, the participants were more likely to initiate positive social interaction with peers after the intervention. Second, the level of shared play of the children increased from the pre-test to the post-test and they all increased the level of collaboration following the intervention. Third, the children with ASD demonstrated lower frequencies of autistic behaviors while using the StoryTable in comparison to the free construction game activity. The implications of these findings are discussed in terms of the effectiveness of this intervention for higher functioning children with ASD.     

Awareness marks: adaptive services through user interactions with augmented objects

The ambient intelligence paradigm involves one important challenge: to be adaptive to users and context through simple and natural interactions. To meet this goal, it is important to associate data with relevant everyday objects in the environment, including users themselves, and to enable interaction mechanisms between these objects. Following this premise, in this paper, we present a conceptual model to link contextual information with augmented elements acquired from user interactions in an implicit and transparent way. In this way, it is possible to personalize and enhance offered services in order to facilitate daily user activities. We call this contextual data “awareness marks”, and these awareness marks make it possible to offer novel services adapted from past events that were captured as they happened. Moreover, we have developed and evaluated a set of prototypes using Near Field Communication technology, which follows the presented model.