40,728 research outputs found

    Deep learning for video game playing

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    In this article, we review recent Deep Learning advances in the context of how they have been applied to play different types of video games such as first-person shooters, arcade games, and real-time strategy games. We analyze the unique requirements that different game genres pose to a deep learning system and highlight important open challenges in the context of applying these machine learning methods to video games, such as general game playing, dealing with extremely large decision spaces and sparse rewards

    RaidEnv: Exploring New Challenges in Automated Content Balancing for Boss Raid Games

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    The balance of game content significantly impacts the gaming experience. Unbalanced game content diminishes engagement or increases frustration because of repetitive failure. Although game designers intend to adjust the difficulty of game content, this is a repetitive, labor-intensive, and challenging process, especially for commercial-level games with extensive content. To address this issue, the game research community has explored automated game balancing using artificial intelligence (AI) techniques. However, previous studies have focused on limited game content and did not consider the importance of the generalization ability of playtesting agents when encountering content changes. In this study, we propose RaidEnv, a new game simulator that includes diverse and customizable content for the boss raid scenario in MMORPG games. Additionally, we design two benchmarks for the boss raid scenario that can aid in the practical application of game AI. These benchmarks address two open problems in automatic content balancing, and we introduce two evaluation metrics to provide guidance for AI in automatic content balancing. This novel game research platform expands the frontiers of automatic game balancing problems and offers a framework within a realistic game production pipeline.Comment: 14 pages, 6 figures, 6 tables, 2 algorithm

    The Curative Power of Play: The Voices of Therapists around the World

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    It is important for all therapists to be culturally sensitive to children and their eco-systems as well as to be aware of the current trends and the changing application of play as a healing agent. The focus of this study is on the development of a current description of play by therapists from a global perspective through a thematic analysis of focus groups resulting in an explanation of how play contributes to healing and the practice of therapy. In this study, the naturalistic method of qualitative research (Bowers, 2009; Lincoln & Guba, 1985) was applied to the study of play around the world, resulting in a new description of “play”. The analyses of focus group meetings in Morocco, Singapore, Hong Kong, Canada and Europe resulted in the emergence of 8 themes: productivity through play, contribution to development, facilitation of the relationship through play, honouring diversity, collaboration between children and caregivers, stimulation through technology-based play, relaxation provided by play, and the devaluation of play. These themes, which are presented through the “voices of the participants”, together with the literature review, serve to enrich the changing description of play. With participants from all continents, a current global perspective highlights the changes that play, both as a concept and as a healing agent, has undergone and will continue to do so. New information emerged suggesting that technology has become a worldwide focus for children but has a paradoxical effect on their relationships

    The UK Netball Superleague: A case study of franchising in elite women's sport organisations

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    This is an Author's Accepted Manuscript of an article published in European Sport Management Quarterly, 12(5), 545 - 567, 2012, copyright Taylor & Francis, available online at: http://www.tandfonline.com/10.1080/16184742.2012.734525.This paper draws on theories of franchising in examining the emergence of the UK Netball Superleague (UK NSL) in 2005. The focus of the paper is to explore the development of an empowered franchise framework as part of England Netball's elite performance strategy and the consequences of the Superleague for player performance, team success and commercial potential of the franchises. Twenty-two in-depth interviews conducted between 2008 and 2011 with franchise and sport media/marketing personnel inform the discussion. The paper explains the UK NSL as an empowered franchise model characterised by a shift from the centralised hierarchical model of the business format franchise to one which is decentralised and informal and whereby different franchises are characterised by high degrees of diversity in terms of organisational environment and their own structural characteristics of specialisation and standardisation.The Centre for Sport, Physical Education and Activity Research (SPEAR) at Canterbury Christ Church University

    Stochastic Prediction of Multi-Agent Interactions from Partial Observations

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    We present a method that learns to integrate temporal information, from a learned dynamics model, with ambiguous visual information, from a learned vision model, in the context of interacting agents. Our method is based on a graph-structured variational recurrent neural network (Graph-VRNN), which is trained end-to-end to infer the current state of the (partially observed) world, as well as to forecast future states. We show that our method outperforms various baselines on two sports datasets, one based on real basketball trajectories, and one generated by a soccer game engine.Comment: ICLR 2019 camera read
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