1,447 research outputs found
âIMPLICIT CREATIONâ â NON-PROGRAMMER CONCEPTUAL MODELS FOR AUTHORING IN INTERACTIVE DIGITAL STORYTELLING
Interactive Digital Storytelling (IDS) constitutes a research field that emerged from several areas of art, creation and computer science. It inquires technologies and possible artefacts that allow âhighly-interactiveâ experiences of digital worlds with compelling stories. However, the situation for story creators approaching âhighly-interactiveâ storytelling is complex. There is a gap between the available technology, which requires programming and prior knowledge in Artificial Intelligence, and established models of storytelling, which are too linear to have the potential to be highly interactive. This thesis reports on research that lays the ground for bridging this gap, leading to novel creation philosophies in future work.
A design research process has been pursued, which centred on the suggestion of conceptual models, explaining a) process structures of interdisciplinary development, b) interactive story structures including the user of the interactive story system, and c) the positioning of human authors within semi-automated creative processes. By means of âimplicit creationâ, storytelling and modelling of simulated worlds are reconciled.
The conceptual models are informed by exhaustive literature review in established neighbouring disciplines. These are a) creative principles in different storytelling domains, such as screenwriting, video game writing, role playing and improvisational theatre, b) narratological studies of story grammars and structures, and c) principles of designing interactive systems, in the areas of basic HCI design and models, discourse analysis in conversational systems, as well as game- and simulation design.
In a case study of artefact building, the initial models have been put into practice, evaluated and extended. These artefacts are a) a conceived authoring tool (âScenejoâ) for the creation of digital conversational stories, and b) the development of a serious game (âThe Killer Phrase Gameâ) as an application development. The study demonstrates how starting out from linear storytelling, iterative steps of âimplicit creationâ can lead to more variability and interactivity in the designed interactive story. In the concrete case, the steps included abstraction of dialogues into conditional actions, and creating a dynamic world model of the conversation. This process and artefact can be used as a model illustrating non-programmer approaches to âimplicit creationâ in a learning process.
Research demonstrates that the field of Interactive Digital Storytelling still has to be further advanced until general creative principles can be fully established, which is a long-term endeavour, dependent upon environmental factors. It also requires further technological developments. The gap is not yet closed, but it can be better explained. The research results build groundwork for education of prospective authors. Concluding the thesis, IDS-specific creative principles have been proposed for evaluation in future work
Towards a crowdsourced solution for the authoring bottleneck in interactive narratives
Interactive Storytelling research has produced a wealth of technologies that can be
employed to create personalised narrative experiences, in which the audience takes
a participating rather than observing role. But so far this technology has not led
to the production of large scale playable interactive story experiences that realise
the ambitions of the field. One main reason for this state of affairs is the difficulty
of authoring interactive stories, a task that requires describing a huge amount of
story building blocks in a machine friendly fashion. This is not only technically
and conceptually more challenging than traditional narrative authoring but also a
scalability problem.
This thesis examines the authoring bottleneck through a case study and a literature
survey and advocates a solution based on crowdsourcing. Prior work has already
shown that combining a large number of example stories collected from crowd workers
with a system that merges these contributions into a single interactive story can be
an effective way to reduce the authorial burden. As a refinement of such an approach,
this thesis introduces the novel concept of Crowd Task Adaptation. It argues that in
order to maximise the usefulness of the collected stories, a system should dynamically
and intelligently analyse the corpus of collected stories and based on this analysis
modify the tasks handed out to crowd workers.
Two authoring systems, ENIGMA and CROSCAT, which show two radically different
approaches of using the Crowd Task Adaptation paradigm have been implemented and
are described in this thesis. While ENIGMA adapts tasks through a realtime dialog
between crowd workers and the system that is based on what has been learned from
previously collected stories, CROSCAT modifies the backstory given to crowd workers
in order to optimise the distribution of branching points in the tree structure that
combines all collected stories. Two experimental studies of crowdsourced authoring
are also presented. They lead to guidelines on how to employ crowdsourced authoring
effectively, but more importantly the results of one of the studies demonstrate the
effectiveness of the Crowd Task Adaptation approach
Unmasking Clever Hans Predictors and Assessing What Machines Really Learn
Current learning machines have successfully solved hard application problems,
reaching high accuracy and displaying seemingly "intelligent" behavior. Here we
apply recent techniques for explaining decisions of state-of-the-art learning
machines and analyze various tasks from computer vision and arcade games. This
showcases a spectrum of problem-solving behaviors ranging from naive and
short-sighted, to well-informed and strategic. We observe that standard
performance evaluation metrics can be oblivious to distinguishing these diverse
problem solving behaviors. Furthermore, we propose our semi-automated Spectral
Relevance Analysis that provides a practically effective way of characterizing
and validating the behavior of nonlinear learning machines. This helps to
assess whether a learned model indeed delivers reliably for the problem that it
was conceived for. Furthermore, our work intends to add a voice of caution to
the ongoing excitement about machine intelligence and pledges to evaluate and
judge some of these recent successes in a more nuanced manner.Comment: Accepted for publication in Nature Communication
Novice programming environments: lowering the barriers, supporting the progression
In 2011, the author published an article that looked at the state of the art in novice programming environments. At the time, there had been an increase in the number of programming environments that were freely available for use by novice programmers, particularly children and young people. What was interesting was that they offered a relatively sophisticated set of development and support features within motivating and engaging environments, where programming could be seen as a means to a creative end, rather than an end in itself. Furthermore, these environments incorporated support for the social and collaborative aspects of learning. The article considered five environmentsâScratch, Alice, Looking Glass, Greenfoot, and Flipâ examining their characteristics and investigating the opportunities they might offer to educators and learners alike. It also considered the broader implications of such environments for both teaching and research. In this chapter, the author revisits the same five environments, looking at how they have changed in the intervening years. She considers their evolution in relation to changes in the field more broadly (e.g., an increased focus on âprogramming for allâ) and reflects on the implications for teaching, as well as research and further development
Lecture Notes on Interactive Storytelling
These lecture notes collect the material used in the advanced course 'Interactive Storytelling' organized biannually at the Department of Future Technologies, University of Turku, Finland. Its aim is to present the key concepts behind interactive digital storytelling (IDS) as well as to review proposed and existing IDS systems. The course focuses on the four partakers of IDS: the platform, the designer, the interactor, and the storyworld. When constructing a platform, the problem is to select an appropriate approach from tightly controlled to emergent storytelling. On this platform, the designer is then responsible for creating the content (e.g., characters, props, scenes and events) for the storyworld, which is then experienced and influenced by the interactor. The structure and relationships between these partakers is explained from a theoretical perspective as well as using existing IDS systems as examples.</p
BPCoach: Exploring Hero Drafting in Professional MOBA Tournaments via Visual Analytics
Hero drafting for multiplayer online arena (MOBA) games is crucial because
drafting directly affects the outcome of a match. Both sides take turns to
"ban"/"pick" a hero from a roster of approximately 100 heroes to assemble their
drafting. In professional tournaments, the process becomes more complex as
teams are not allowed to pick heroes used in the previous rounds with the
"best-of-N" rule. Additionally, human factors including the team's familiarity
with drafting and play styles are overlooked by previous studies. Meanwhile,
the huge impact of patch iteration on drafting strengths in the professional
tournament is of concern. To this end, we propose a visual analytics system,
BPCoach, to facilitate hero drafting planning by comparing various drafting
through recommendations and predictions and distilling relevant human and
in-game factors. Two case studies, expert feedback, and a user study suggest
that BPCoach helps determine hero drafting in a rounded and efficient manner.Comment: Accepted by The 2024 ACM SIGCHI Conference on Computer-Supported
Cooperative Work & Social Computing (CSCW) (Proc. CSCW 2024
SCALING REINFORCEMENT LEARNING THROUGH FEUDAL MULTI-AGENT HIERARCHY
Militaries conduct wargames for training, planning, and research purposes. Artificial intelligence (AI) can improve military wargaming by reducing costs, speeding up the decision-making process, and offering new insights. Previous researchers explored using reinforcement learning (RL) for wargaming based on the successful use of RL for other human competitive games. While previous research has demonstrated that an RL agent can generate combat behavior, those experiments have been limited to small-scale wargames. This thesis investigates the feasibility and acceptability of -scaling hierarchical reinforcement learning (HRL) to support integrating AI into large military wargames. Additionally, this thesis also investigates potential complications that arise when replacing the opposing force with an intelligent agent by exploring the ways in which an intelligent agent can cause a wargame to fail. The resources required to train a feudal multi-agent hierarchy (FMH) and a standard RL agent and their effectiveness are compared in increasingly complicated wargames. While FMH fails to demonstrate the performance required for large wargames, it offers insight for future HRL research. Finally, the Department of Defense verification, validation, and accreditation process is proposed as a method to ensure that any future AI application applied to wargames are suitable.Lieutenant Colonel, United States ArmyApproved for public release. Distribution is unlimited
Towards a global participatory platform: Democratising open data, complexity science and collective intelligence
The FuturICT project seeks to use the power of big data, analytic models grounded in complexity science, and the collective intelligence they yield for societal benefit. Accordingly, this paper argues that these new tools should not remain the preserve of restricted government, scientific or corporate Ă©lites, but be opened up for societal engagement and critique. To democratise such assets as a public good, requires a sustainable ecosystem enabling different kinds of stakeholder in society, including but not limited to, citizens and advocacy groups, school and university students, policy analysts, scientists, software developers, journalists and politicians. Our working name for envisioning a sociotechnical infrastructure capable of engaging such a wide constituency is the Global Participatory Platform (GPP). We consider what it means to develop a GPP at the different levels of data, models and deliberation, motivating a framework for different stakeholders to find their ecological niches at different levels within the system, serving the functions of (i) sensing the environment in order to pool data, (ii) mining the resulting data for patterns in order to model the past/present/future, and (iii) sharing and contesting possible interpretations of what those models might mean, and in a policy context, possible decisions. A research objective is also to apply the concepts and tools of complexity science and social science to the project's own work. We therefore conceive the global participatory platform as a resilient, epistemic ecosystem, whose design will make it capable of self-organization and adaptation to a dynamic environment, and whose structure and contributions are themselves networks of stakeholders, challenges, issues, ideas and arguments whose structure and dynamics can be modelled and analysed. Graphical abstrac
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