Comparing Clustering Approaches for Modeling Players' Values through Avatar Construction

Abstract Videogame avatars provide an expressive avenue for players to represent themselves virtually. Research has shown that these avatars, while virtual, can reveal aspects of players' identities, along with physical, social, and cultural values of the real-world. In this paper, we present an approach for modeling player values through their avatars using artificial intelligence (AI) clustering techniques. In a study with 191 participants who created avatars using our system, we provide a thorough comparison of the techniques across numerical, textual, and visual data. Our findings showed that these data structures can effectively reveal players' values and preferences, such as conforming to stereotypes of character roles using statistical attributes, modeling nuances in text descriptions of avatars, and identifying "bestexample" (prototypical) avatar appearances that players can be quantitatively shown to conform to. Our findings suggest that AI clustering approaches can be used to model players to yield insight into implicitly held values in a data-driven manner through virtual avatars

Modeling player self-representation in multiplayer online games using social network data

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 101-105).Game players express values related to self-expression through various means such as avatar customization, gameplay style, and interactions with other players. Multiplayer online games are now often integrated with social networks that provide social contexts in which player-to-player interactions take place, such as conversation and trading of virtual items. Building upon a theoretical framework based in machine learning and cognitive science, I present results from a novel approach to modeling and analyzing player values in terms of both preferences in avatar customization and patterns in social network use. To facilitate this work, I developed the Steam-Player- Preference Analyzer (Steam-PPA) system, which performs advanced data collection on publicly available social networking profile information. The primary contribution of this thesis is the AIR Toolkit Status Performance Classifier (AIR-SPC), which uses machine learning techniques including k-means clustering, natural language processing (NLP), and support vector machines (SVM) to perform inference on the data. As an initial case study, I use Steam-PPA to collect gameplay and avatar customization information from players in the popular, and commercially successful, multi-player first-person-shooter game Team Fortress 2 (TF2). Next, I use AIR-SPC to analyze the information from profiles on the social network Steam. The upshot is that I use social networking information to predict the likelihood of players customizing their profile in several ways associated with the monetary values of their avatars. In this manner I have developed a computational model of aspects of players' digital social identity capable of predicting specific values in terms of preferences exhibited within a virtual game-world.by Chong-U Lim.S.M

Orchestrating Game Generation

The design process is often characterized by and realized through the iterative steps of evaluation and refinement. When the process is based on a single creative domain such as visual art or audio production, designers primarily take inspiration from work within their domain and refine it based on their own intuitions or feedback from an audience of experts from within the same domain. What happens, however, when the creative process involves more than one creative domain such as in a digital game? How should the different domains influence each other so that the final outcome achieves a harmonized and fruitful communication across domains? How can a computational process orchestrate the various computational creators of the corresponding domains so that the final game has the desired functional and aesthetic characteristics? To address these questions, this article identifies game facet orchestration as the central challenge for AI-based game generation, discusses its dimensions and reviews research in automated game generation that has aimed to tackle it. In particular, we identify the different creative facets of games, we propose how orchestration can be facilitated in a top-down or bottom-up fashion, we review indicative preliminary examples of orchestration, and we conclude by discussing the open questions and challenges ahead

The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions

The Metaverse offers a second world beyond reality, where boundaries are non-existent, and possibilities are endless through engagement and immersive experiences using the virtual reality (VR) technology. Many disciplines can benefit from the advancement of the Metaverse when accurately developed, including the fields of technology, gaming, education, art, and culture. Nevertheless, developing the Metaverse environment to its full potential is an ambiguous task that needs proper guidance and directions. Existing surveys on the Metaverse focus only on a specific aspect and discipline of the Metaverse and lack a holistic view of the entire process. To this end, a more holistic, multi-disciplinary, in-depth, and academic and industry-oriented review is required to provide a thorough study of the Metaverse development pipeline. To address these issues, we present in this survey a novel multi-layered pipeline ecosystem composed of (1) the Metaverse computing, networking, communications and hardware infrastructure, (2) environment digitization, and (3) user interactions. For every layer, we discuss the components that detail the steps of its development. Also, for each of these components, we examine the impact of a set of enabling technologies and empowering domains (e.g., Artificial Intelligence, Security & Privacy, Blockchain, Business, Ethics, and Social) on its advancement. In addition, we explain the importance of these technologies to support decentralization, interoperability, user experiences, interactions, and monetization. Our presented study highlights the existing challenges for each component, followed by research directions and potential solutions. To the best of our knowledge, this survey is the most comprehensive and allows users, scholars, and entrepreneurs to get an in-depth understanding of the Metaverse ecosystem to find their opportunities and potentials for contribution

Design and Evaluation of Intelligent Reward Structures in Human Computation Games

Despite the ubiquity of artificial intelligence, some problems and procedures— such as building commonsense knowledge understanding or generating creative works— have no or few effective algorithmic solutions, yet are considered straightforward for humans to solve. Human computation games (HCGs) are playful, game-based interfaces for tackling these problems through crowdsourcing. HCGs have been used to solve tasks that were and still are considered complex for computational algorithms such as image tagging, protein synthesis, 3D structure reconstruction, and creative artifact generation. However, despite these successes, HCGs have not seen broad adoption compared to other types of serious digital games. Among the many reasons for this lack of adoption is the reality that these games are typically not seen as engaging or compelling to play, as well as the fact that creating HCGs comes at a high development cost to task providers who are typically not game development experts. This thesis is a step towards building and establishing a more formalized design understanding of how to create HCGs that both provide a compelling player experience and complete the underlying task effectively. In this thesis, I explore reward mechanics in HCGs. Reward mechanics are integral to HCGs due their associations with player motivation, compensation, and task validation. I first propose a framework for understanding HCG mechanics and advocate for an experimental methodology evaluating both player experience and task completion metrics to understand variations in HCG mechanics. I then use these tools to frame and design three experiments that explore small-scale variations of reward systems in HCGs: reward functions, reward distribution, and reward personalization. These studies demonstrate that even small variations in rewards (i.e., offering players the ability to choose the type of reward) may have significant positive effects on both player experience and task completion metrics. I also show that some variations (i.e., co-located, competitive reward scoring) may have both positive and negative tradeoffs across these metrics. Moreover, this work observes that existing, anecdotal design wisdom for HCGs may not always hold (i.e., allowing players to verbally collude actually predicts higher task solution accuracy). Altogether, this thesis demonstrates that certain aspects of reward systems in HCGs can be varied to improve the player experience without compromising task completion metrics, and builds more empirically-tested design knowledge for creating more engaging, effective HCGs.Ph.D

Customizing Experiences for Mobile Virtual Reality

A criação manual de conteúdo para um jogo é um processo demorado e trabalhoso que requer um conjunto de habilidades diversi cado (normalmente designers, artistas e programadores) e a gestão de diferentes recursos (hardware e software especializados). Dado que o orçamento, tempo e recursos são frequentemente muito limitados, os projetos poderiam bene ciar de uma solução que permitisse poupar e investir noutros aspectos do desenvolvimento. No contexto desta tese, abordamos este desa o sugerindo a criação de pacotes especí cos para a geração de conteúdo per sonalizável, focados em aplicações de Realidade Virtual (RV) móveis. Esta abordagem divide o problema numa solução com duas facetas: em primeiro lugar, a Geração Procedural de Conteúdo, alcançada através de métodos convencionais e pela utilização inovadora de Grandes Modelos de Lin guagem (normalmente conhecidos por Large Language Models). Em segundo lugar, a Co-Criação de Conteúdo, que enfatiza o desenvolvimento colaborativo de conteúdo. Adicionalmente, dado que este trabalho se foca na compatibilidade com RV móvel, as limitações de hardware associadas a capacetes de RV autónomos (standalone VR Headsets) e formas de as ultrapassar são também abordadas. O conteúdo será gerado utilizando métodos actuais em geração procedural e facilitando a co-criação de conteúdo pelo utilizador. A utilização de ambas estas abordagens resulta em ambi entes, objectivos e conteúdo geral mais re-jogáveis com muito menos desenho. Esta abordagem está actualmente a ser aplicada no desenvolvimento de duas aplicações de RV distintas. A primeira, AViR, destina-se a oferecer apoio psicológico a indivíduos após a perda de uma gravidez. A se gunda, EmotionalVRSystem, visa medir as variações nas respostas emocionais dos participantes induzidas por alterações no ambiente, utilizando tecnologia EEG para leituras precisas

Serious game to educate non-experts about energy related design and living

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Architecture, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 99-100).Climate Change is one defining issue of our time. With the increasingly sophisticated uses of energy, we have to face the problem as energy shortage and global warming. Since almost one-fourth of US energy is consumed by homes, creating high-performance low-energy houses and educating people about energy-related decision making, is perhaps the first and most cost-effective way of addressing energy issue. Towards this end, I propose a learning tool to educate non-experts about energy-related design and decision-making of their own homes. This tool, BIM Game, is based on BIM (Building Information Modeling) and E-learning game. By integrating BIM and Serious Game together, the new responsive model can change design education from the professionals to all people who care about energy issue and living environment. Through learning by playing, it is able to create a deep-learning environment and also add emotion to the problem-solving process. It also explores innovative shifts in building industry for consumer participative design and file-to-factory fabrication strategies, change the role of the consumer from the last benefit end-user to the first decision maker. So finally it will take advantage of the inexpensive computation, to raise the public awareness of participative design, energy efficiency, healthy living, and sustainability.by Lin Yang.S.M

The use of machine learning to improve the identification and assessment of internet-related disorders

The Internet's growing significance has raised global concerns about Internet-related disorders. Organizations like the American Psychological Association (APA) and the World Health Organization (WHO) have already highlighted the potential negative effects of excessive Internet use on mental health. Since the inclusion of gaming disorder as a condition for further study in the DSM-5 and its recognition as a mental disorder in ICD-11, research on the problematic use of the Internet (PUI) become a topic of even greater significance. The present PhD thesis aims to address two key research priorities in the field of PUI, formulated by the European Network for PUI, related to (a) contributing to their conceptualization and (b) improving their assessment. In this regard, four different studies targeting gaming disorder and cyberchondria, a condition characterized by excessive and uncontrollable searching for health-related information on the Internet, were deployed. This thesis centrally focuses on using machine learning (ML) and traditional statistics to reach these objectives. In Study 1, the levels of cyberchondria during the pandemic were investigated and compared with the retrospectively assessed pre-pandemic levels. It also identified psychological factors that could predict the level of cyberchondria during the pandemic. In Study 2, different gamer groups based on their profiles of passion for gaming were identified. It also observed how gaming disorder symptoms, assessed within the substance use disorder and gambling frameworks (e.g., tolerance, withdrawal, preoccupation, mood modification), are linked to harmonious and/or an obsessive passion for gaming. Study 3 used gaming disorder criteria to predict depression and well-being levels. It also identified predictors of gaming disorder level and their importance in the prediction of each DSM-5 criterion proposed for Internet gaming disorder. Finally, Study 4 warns against the misuse of algorithm-generated data in ML analyses and its negative impact on the conceptualization and assessment of a PUI. Results from the studies suggest that cyberchondria and gaming disorder can be understood within the same general framework. Nevertheless, additional models specific to each condition can enhance their understanding and provide important insights for their treatment and prevention interventions. Regarding their assessment, the thesis supports the idea of a possible transdiagnostic nature of the criteria proposed by the ICD-11 for the assessment of gaming disorder and their potential capacity to address the various forms of PUI. The thesis also demonstrates that ML methodologies offer a helpful and convenient instrument for psychological research topics such as the PUI.R-AGR-3440 - PRIDE17/12252781 DRIVEN_Common - ZILIAN Andrea