35,778 research outputs found
Tangible user interfaces : past, present and future directions
In the last two decades, Tangible User Interfaces (TUIs) have emerged as a new interface type that interlinks the digital and physical worlds. Drawing upon users' knowledge and skills of interaction with the real non-digital world, TUIs show a potential to enhance the way in which people interact with and leverage digital information. However, TUI research is still in its infancy and extensive research is required in or- der to fully understand the implications of tangible user interfaces, to develop technologies that further bridge the digital and the physical, and to guide TUI design with empirical knowledge. This paper examines the existing body of work on Tangible User In- terfaces. We start by sketching the history of tangible user interfaces, examining the intellectual origins of this field. We then present TUIs in a broader context, survey application domains, and review frame- works and taxonomies. We also discuss conceptual foundations of TUIs including perspectives from cognitive sciences, phycology, and philoso- phy. Methods and technologies for designing, building, and evaluating TUIs are also addressed. Finally, we discuss the strengths and limita- tions of TUIs and chart directions for future research
OPEB: Open Physical Environment Benchmark for Artificial Intelligence
Artificial Intelligence methods to solve continuous- control tasks have made
significant progress in recent years. However, these algorithms have important
limitations and still need significant improvement to be used in industry and
real- world applications. This means that this area is still in an active
research phase. To involve a large number of research groups, standard
benchmarks are needed to evaluate and compare proposed algorithms. In this
paper, we propose a physical environment benchmark framework to facilitate
collaborative research in this area by enabling different research groups to
integrate their designed benchmarks in a unified cloud-based repository and
also share their actual implemented benchmarks via the cloud. We demonstrate
the proposed framework using an actual implementation of the classical
mountain-car example and present the results obtained using a Reinforcement
Learning algorithm.Comment: Accepted in 3rd IEEE International Forum on Research and Technologies
for Society and Industry 201
Engaging the 'Xbox generation of learners' in Higher Education
The research project identifies examples of technology used to empower learning of Secondary school pupils that could be used to inform students’ engagement in learning with technology in the Higher Education sector.
Research was carried out in five partnership Secondary schools and one associate Secondary school to investigate how pupils learn with technology in lessons and to identify the pedagogy underpinning such learning. Data was collected through individual interviews with pupils, group interviews with members of the schools’ councils, lesson observations, interviews with teachers, pupil surveys, teacher surveys, and a case study of a learning event.
In addition, data was collected on students’ learning with technology at the university through group interviews with students and student surveys in the School of Education and Professional Development, and through surveys completed by students across various university departments.
University tutors, researchers, academic staff, learning technology advisers, and cross sector partners from the local authority participated in focus group interviews on the challenges facing Higher Education in engaging new generations of students, who have grown up in the digital age, in successful scholarly learning
Automated Game Design Learning
While general game playing is an active field of research, the learning of
game design has tended to be either a secondary goal of such research or it has
been solely the domain of humans. We propose a field of research, Automated
Game Design Learning (AGDL), with the direct purpose of learning game designs
directly through interaction with games in the mode that most people experience
games: via play. We detail existing work that touches the edges of this field,
describe current successful projects in AGDL and the theoretical foundations
that enable them, point to promising applications enabled by AGDL, and discuss
next steps for this exciting area of study. The key moves of AGDL are to use
game programs as the ultimate source of truth about their own design, and to
make these design properties available to other systems and avenues of inquiry.Comment: 8 pages, 2 figures. Accepted for CIG 201
"A step into the abyss" Transmedia in the UK Games and Television Industries
This article uses a media industries studies perspective to investigate the current state of transmedia production in the UK. Analysing the discursive statements of a range of industry participants from both UK television and games industries, the article reveals a series of contradictions and misunderstandings that may be limiting the effectiveness of multi-platform projects. By comparing overlapping discursive patterns around attitudes to risk, measures of success, authorship between the two industries, and repeated concerns over the balance of creative and commercial imperatives, the article argues that existing hierarchies of power between media industries threaten to derail future convergence
AI Researchers, Video Games Are Your Friends!
If you are an artificial intelligence researcher, you should look to video
games as ideal testbeds for the work you do. If you are a video game developer,
you should look to AI for the technology that makes completely new types of
games possible. This chapter lays out the case for both of these propositions.
It asks the question "what can video games do for AI", and discusses how in
particular general video game playing is the ideal testbed for artificial
general intelligence research. It then asks the question "what can AI do for
video games", and lays out a vision for what video games might look like if we
had significantly more advanced AI at our disposal. The chapter is based on my
keynote at IJCCI 2015, and is written in an attempt to be accessible to a broad
audience.Comment: in Studies in Computational Intelligence Studies in Computational
Intelligence, Volume 669 2017. Springe
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