
IT University of Copenhagen
IT University of Copenhagen
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91 Projects, page 1 of 19
Open Access Mandate for Publications and Research data assignment_turned_in Project2024 - 2026Partners:IT University of CopenhagenIT University of CopenhagenFunder: European Commission Project Code: 101154545Funder Contribution: 230,774 EURAffective gaming - or gameplay that is influenced by a player's emotional state - is a research domain at the intersection of HCI and affective computing; yet the field has stagnated over the years since its inception back in the early 1980s. In RAGE, I will revitalize the field of affective gaming by addressing foundational epistemic problems that are contributing to this stagnation. RAGE’s research objectives tackle explicating unclear and hidden assumptions and value sets in this space, and the practical tensions that exist in terms of implementation. I analyze the field through both a theoretical lens in the first year, and moving to a practical implementation of affective games in the second. In this project, I will transfer my knowledge in designing and creating affective games for the implementation aspects of RAGE while Prof. Elisa Mekler (ITU Copenhagen, Denmark) will support the theory aspects. With this fundamentally interdisciplinary project, I will collaborate with and connect many research groups and labs at ITU from different disciplines, including the Center for Digital Play, the Affective Interactions and Relations (AIR) lab, and the Interaction design (IxD) lab. Collaboration within this interdisciplinary team and broadening my research portfolio to include theoretical and critical research will allow me to shape a research vision and establish myself as a key researcher of affective gaming within the EU, in service of my eventual goal to lead my own research group within the EU.
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For further information contact us at helpdesk@openaire.euassignment_turned_in Project2009 - 2012Partners:IT University of CopenhagenIT University of CopenhagenFunder: European Commission Project Code: 249322All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=corda_______::b4176524122782a44be3ee3465971297&type=result"></script>'); --> </script>
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For further information contact us at helpdesk@openaire.euOpen Access Mandate for Publications assignment_turned_in Project2016 - 2022Partners:IT University of CopenhagenIT University of CopenhagenFunder: European Commission Project Code: 695528Overall Budget: 2,006,910 EURFunder Contribution: 2,006,910 EURMaking Sense of Games (MSG) will build a methodology for the humanistic study of games, and develop a theory of how ludic meaning is produced. Following the pervasive, global growth of video gaming culture and the games industry, the multi-disciplinary field of game studies has grown exponentially in the last 15 years, with numerous new journals, conferences, university programs and research departments. However, still lacking at this ‘adolescent’ stage of the field’s development are game-specific methods and theoretical foundations necessary to train researchers and build curricula. In aesthetic games research there is not yet any widely accepted methodology for game analysis, and there has not yet been any large-scale, long-term attempt to produce a theoretical platform that can support and advance the field. MSG aims to fill this gap by combining fundamental hermeneutic approaches (semiotics, reception theory, reader response, theories of representation, narrative theory) with recent theories of ludic structure (game ontology) into a hermeneutic theory of game meaning, which can be used as a set of tools and concepts for game analysis and criticism. MSG will be a triple first for aesthetic game research: a five-year research program, a hermeneutic theory of games, and a team-based effort to build an interdisciplinary methodology. The results from MSG will speak to many of the current public concerns and debates about games, such as gamer culture, games’ cultural and artistic status, the representation of minorities, misogyny, violence and even addiction. MSG will demonstrate the strong usefulness of humanistic approaches not only to game studies itself, but also to the 21st century’s most vibrant new cultural sector. It will also provide other aesthetic fields (literary studies, film studies, art history) with theoretical models, critical insights, and a rich empirical material for comparative exploration.
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For further information contact us at helpdesk@openaire.euOpen Access Mandate for Publications and Research data assignment_turned_in Project2025 - 2030Partners:IT University of CopenhagenIT University of CopenhagenFunder: European Commission Project Code: 101161734Overall Budget: 1,498,760 EURFunder Contribution: 1,498,760 EURWelfare systems rely on extensive knowledge about the population to plan, finance, and expend limited resources in a targeted manner. In view of their often-fragmented national identification and statistical systems, Africa’s emerging welfare states are thus facing significant challenges in their capacity to establish categories of welfare entitlement and to target groups for intervention. Led by the PI, ModelFutures’ team will carry out ground-breaking, comparative ethnographic research at the statistics-welfare nexus of four African country cases – Ghana, Senegal, Kenya and Botswana – to understand: How do states generate truths about future welfare in contexts of uncertain knowledge about the population and its wellbeing? The project’s threefold objectives aim to (1) trace statistical modelling practices in the context of multi-facetted uncertainties about the population and its environs; (2) analyse the impact of adaptations and creative data practices on quantitative truth claims; and (3) connect statistical future-making and anticipatory welfare politics in sites of statistical innovation. ModelFutures’ ambition significantly extends beyond the state of the art of our understanding of statistical world-making by developing a novel concept of vernacular prediction that attunes to experts’ skilful adaptations of globally circulating computational models and standards, while attending to their modelling practices’ co-constitution with symbolic commitments and situated infrastructural arrangements. Combining expertise from anthropology, science and technology studies, and population statistics, ModelFutures generates novel theory on the production of evidence-based welfare policies in contexts of contested claims to the validity of data, methods, and the anticipatory politics that play out between short-term mitigation efforts and the pursuit of long-term dividends.
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For further information contact us at helpdesk@openaire.euOpen Access Mandate for Publications and Research data assignment_turned_in Project2023 - 2027Partners:IT University of CopenhagenIT University of CopenhagenFunder: European Commission Project Code: 101045094Overall Budget: 1,994,220 EURFunder Contribution: 1,994,220 EURDespite major advances in the field of artificial intelligence, especially in the field of neural networks, these systems still pale in comparison to even simple biological intelligence. Current machine learning systems take many trials to learn, lack common-sense, and often fail even if the environment only changes slightly. The enormous potential of autonomous machines remains unfulfilled and we still lack robots to fill our dishwashers or go on autonomous search-and-rescue missions. The grand goal of GROW-AI is to create machines with a more general intelligence, allowing rapid adaption in unknown situations. In stark contrast to current neural networks, whose architectures are designed by human experts and whose large number of parameters are optimized directly, evolution does not operate directly on the parameters of biological nervous systems. Instead, these nervous systems are grown and self-organize through a much smaller genetic program that produces rich behavioral capabilities right from birth and the ability to rapidly learn. Neuroscience suggests this "genomic bottleneck" is an important regularizing constraint, allowing animals to generalize to new situations. However, currently there does not exist a solution to creating a similar system artificially. We address this challenge with two ambitious ideas. First, we will learn genomic bottleneck algorithms instead of manually designing them, exploiting recent advances in memory-augmented deep neural networks that can learn complex algorithms. In addition, we will co-optimize task generators that provide the agents with the most effective learning environments. Taking inspiration from the fields of artificial life, neurobiology, and machine learning, we will investigate if algorithmic growth is needed to understand and create intelligence. If successful, this project will greatly improve the autonomy of machines and significantly increase the range of real-world tasks they can solve.
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