111 research outputs found

    How to Be a God

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    When it comes to questions concerning the nature of Reality, Philosophers and Theologians have the answers. Philosophers have the answers that can’t be proven right. Theologians have the answers that can’t be proven wrong. Today’s designers of Massively-Multiplayer Online Role-Playing Games create realities for a living. They can’t spend centuries mulling over the issues: they have to face them head-on. Their practical experiences can indicate which theoretical proposals actually work in practice. That’s today’s designers. Tomorrow’s will have a whole new set of questions to answer. The designers of virtual worlds are the literal gods of those realities. Suppose Artificial Intelligence comes through and allows us to create non-player characters as smart as us. What are our responsibilities as gods? How should we, as gods, conduct ourselves? How should we be gods

    Unrealisticness

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    Virtual worlds are works of fiction. As such, they treat as true propositions which are known to be false (such as “magic works” and “dragons exist”). Any propositions not covered by the fiction derive their truth or falsehood from the world in which we live (such as “gravity works” and “spectacles exist”). However, some statements are true within the virtual world that are addressed by neither the fiction nor the non-fiction that it overrides. These contextually-unsupported statements are said to be unrealistic. Their impact on the player is generally negative, because it undermines the player’s trust in the virtual world. However, if their presence serves to show that the virtual world admits its fallibility, then the result can in the end be positive

    Massively Multiplayer Storytelling

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    The 2018 Hanabi competition

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    This paper outlines the Hanabi competition, first run at CIG 2018, and returning for COG 2019. Hanabi presents a useful domain for game agents which must function in a cooperative environment. The paper presents the results of the two tracks which formed the 2018 competition and introduces the learning track, a new track for 2019 which allows the agents to collect statistics across multiple games

    A Framework and Taxonomy of Videogame Playing Preferences

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    © Owners/Authors, 2017. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in CHI PLAY '17 - Proceedings of the Annual Symposium on Computer-Human Interaction in Play.Player preferences for different gaming styles or game elements has been a topic of interest in human-computer interaction for over a decade. However, current models suggested by the extant literature are generally based on classifying abstract gaming motivations or player archetypes. These concepts do not directly map onto the building blocks of games, taking away from the utility of the findings. To address this issue, we propose a conceptual framework of player preferences based on two dimensions: game elements and game playing styles. To investigate these two concepts, we conducted an exploratory empirical investigation of player preferences, which allowed us to create a taxonomy of nine groups of game elements and five groups of game playing styles. These two concepts are foundational to games, which means that our model can be used by designers to create games that are tailored to their target audience. In addition, we demonstrate that there are significant effects of gender and age on participants’ preferences and discuss the implications of these findings.NSERC || RGPIN-418622-2012 SSHRC || 895-2011-1014, IMMERSe CFI || 35819 Mitacs || IT07255 SWaGUR CNPq, Brazi

    Social gamification in enterprise crowdsourcing

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    Enterprise crowdsourcing capitalises on the availability of employ-ees for in-house data processing. Gamification techniques can help aligning employees’ motivation to the crowdsourcing endeavour. Although hitherto, research efforts were able to unravel the wide arsenal of gamification techniques to construct engagement loops, little research has shed light into the social game dynamics that those foster and how those impact crowdsourcing activities. This work reports on a study that involved 101 employees from two multinational enterprises. We adopt a user-centric approach to ap-ply and experiment with gamification for enterprise crowdsourcing purposes. Through a qualitative study, we highlight the importance of the competitive and collaborative social dynamics within the enterprise. By engaging the employees with a mobile crowdsourc-ing application, we showcase the effectiveness of competitiveness towards higher levels of engagement and quality of contributions. Moreover, we underline the contradictory nature of those dynam-ics, which combined might lead to detrimental effects towards the engagement to crowdsourcing activities

    Elements of Gameful Design Emerging from User Preferences

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    © Owners/Authors, 2017. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in CHI PLAY '17 - Proceedings of the Annual Symposium on Computer-Human Interaction in Play.Several studies have developed models to explain player preferences. These models have been developed for digital games; however, they have been frequently applied in gameful design (i.e., designing non-game applications with game elements) without empirical validation of their fit to this different context. It is not clear if users experience game elements embedded in applications similarly to how players experience them in games. Consequently, we still lack a conceptual framework of design elements built specifically for a gamification context. To fill this gap, we propose a classification of eight groups of gameful design elements produced from an exploratory factor analysis based on participants’ self-reported preferences. We describe the characteristics of the users who are more likely to enjoy each group of design elements in terms of their gender, age, gamification user type, and personality traits. Our main contribution is providing an overview of which design elements work best for what demographic clusters and how we can apply this knowledge to design effective gameful systems.SSHRC || 895-2011-1014, IMMERSe NSERC || RGPIN-418622-2012 CFI || 35819 Mitacs || IT07255 CNPq, Brazil AgĂšncia de GestiĂł d’Ajuts Universitaris i de Recerca (Generalitat de Catalunya) || Industrial Doctorate programme 2014-DI-00

    Distributed Social Multi-Agent Negotiation Framework For Incomplete Information Games

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    In this paper, we propose a social negotiation system in which agents can communicate and interact with each other socially throughout a Sheriff of Nottingham game. We address issues with the number of options available while negotiating, particularly when bluffing is involved. Experiments are proposed that would allow us to validate how closely this framework mirrors real social interaction in the game, and the possibility of generalising multi-agent negotiation beyond this framework is raised

    Do automated digital health behaviour change interventions have a positive effect on self-efficacy? A systematic review and meta-analysis

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    © 2019 Taylor & Francis. This is an Accepted Manuscript of an article published by Taylor & Francis in Health Psychology Review on 20/01/2020, available online: https://doi.org/10.1080/17437199.2019.1705873.Self-efficacy is an important determinant of health behaviour. Digital interventions are a potentially acceptable and cost-effective way of delivering programmes of health behaviour change at scale. Whether behaviour change interventions work to increase self-efficacy in this context is unknown. This systematic review and meta-analysis sought to identify whether automated digital interventions are associated with positive changes in self-efficacy amongst non-clinical populations for five major health behaviours, and which BCTs are associated with that change. A systematic literature search identified 20 studies (n=5624) that assessed changes in self-efficacy and were included in a random effects meta-analysis. Interventions targeted: healthy eating (k=4), physical activity (k=9), sexual behaviour (k=3), and smoking (k=4). No interventions targeting alcohol use were identified. Overall, interventions had a small, positive effect on self-efficacy (푔 = 0.190, CI [0.078; 0.303]). The effect of interventions on self-efficacy did not differ as a function of health behaviour type (Qbetween = 7.3704 p = 0.061, df = 3). Inclusion of the BCT ‘information about social and environmental consequences’ had a small, negative effect on self-efficacy (Δ푔= - 0.297, Q=7.072, p=0.008). Whilst this review indicates that digital interventions can be used to change self-efficacy, which techniques work best in this context is not clear.Peer reviewedFinal Accepted Versio

    Moment-to-moment Engagement Prediction through the Eyes of the Observer: PUBG Streaming on Twitch

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    Is it possible to predict moment-to-moment gameplay engagement based solely on game telemetry? Can we reveal engaging moments of gameplay by observing the way the viewers of the game behave? To address these questions in this paper, we reframe the way gameplay engagement is defined and we view it, instead, through the eyes of a game's live audience. We build prediction models for viewers' engagement based on data collected from the popular battle royale game PlayerUnknown's Battlegrounds as obtained from the Twitch streaming service. In particular, we collect viewers' chat logs and in-game telemetry data from several hundred matches of five popular streamers (containing over 100,000 game events) and machine learn the mapping between gameplay and viewer chat frequency during play, using small neural network architectures. Our key findings showcase that engagement models trained solely on 40 gameplay features can reach accuracies of up to 80% on average and 84% at best. Our models are scalable and generalisable as they perform equally well within- and across-streamers, as well as across streamer play styles.Comment: Version accepted for the Conference on the Foundations of Digital Games 2020 - Malt
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