Dagstuhl Reports : Volume 1, Issue 2, February 2011

Online Privacy: Towards Informational Self-Determination on the Internet (Dagstuhl Perspectives Workshop 11061) : Simone Fischer-Hübner, Chris Hoofnagle, Kai Rannenberg, Michael Waidner, Ioannis Krontiris and Michael Marhöfer Self-Repairing Programs (Dagstuhl Seminar 11062) : Mauro Pezzé, Martin C. Rinard, Westley Weimer and Andreas Zeller Theory and Applications of Graph Searching Problems (Dagstuhl Seminar 11071) : Fedor V. Fomin, Pierre Fraigniaud, Stephan Kreutzer and Dimitrios M. Thilikos Combinatorial and Algorithmic Aspects of Sequence Processing (Dagstuhl Seminar 11081) : Maxime Crochemore, Lila Kari, Mehryar Mohri and Dirk Nowotka Packing and Scheduling Algorithms for Information and Communication Services (Dagstuhl Seminar 11091) Klaus Jansen, Claire Mathieu, Hadas Shachnai and Neal E. Youn

Let's mix it up: interviews exploring the practical and technical challenges of interactive mixing in games

Game audio has come a long way since the simple electronic beeps of the early 1970s, when significant technical constraints governed the scope of creative possibilities. Recent years have witnessed technological advancements on an unprecedented scale; no sooner is one technology introduced than it is superseded by another, boasting a range of new refinements and enhanced performance

Analysing qualitative data from virtual worlds: using images and text mining

There is an increasing interest within both organisational and social contexts in virtual worlds and virtual reality platforms. Virtual worlds are highly graphical systems in which avatars interact with each other, and almost every event and conversation is logged and recorded. This presents new challenges for qualitative researchers in information systems. This paper addresses the challenges of analyzing the huge amounts of qualitative data that can be obtained from virtual worlds (both images and text). It addresses how images might be used in qualitative studies of virtual worlds, and proposes a new way to analyze textual data using a qualitative software tool called Leximancer. This paper illustrates these methods using a study of a social movement in a virtual world

The Cowl - v.52 - n.14 - Feb 17, 1988

The Cowl - student newspaper of Providence College. Vol 52 - No. 14 - February 17, 1988. 24 pages

Techniques to Understand Computer Simulations: Markov Chain Analysis

The aim of this paper is to assist researchers in understanding the dynamics of simulation models that have been implemented and can be run in a computer, i.e. computer models. To do that, we start by explaining (a) that computer models are just input-output functions, (b) that every computer model can be re-implemented in many different formalisms (in particular in most programming languages), leading to alternative representations of the same input-output relation, and (c) that many computer models in the social simulation literature can be usefully represented as time-homogeneous Markov chains. Then we argue that analysing a computer model as a Markov chain can make apparent many features of the model that were not so evident before conducting such analysis. To prove this point, we present the main concepts needed to conduct a formal analysis of any time-homogeneous Markov chain, and we illustrate the usefulness of these concepts by analysing 10 well-known models in the social simulation literature as Markov chains. These models are: • Schelling\'s (1971) model of spatial segregation • Epstein and Axtell\'s (1996) Sugarscape • Miller and Page\'s (2004) standing ovation model • Arthur\'s (1989) model of competing technologies • Axelrod\'s (1986) metanorms models • Takahashi\'s (2000) model of generalized exchange • Axelrod\'s (1997) model of dissemination of culture • Kinnaird\'s (1946) truels • Axelrod and Bennett\'s (1993) model of competing bimodal coalitions • Joyce et al.\'s (2006) model of conditional association In particular, we explain how to characterise the transient and the asymptotic dynamics of these computer models and, where appropriate, how to assess the stochastic stability of their absorbing states. In all cases, the analysis conducted using the theory of Markov chains has yielded useful insights about the dynamics of the computer model under study.Computer Modelling, Simulation, Markov, Stochastic Processes, Analysis, Re-Implementation

Why Are We Permanently Stuck in an Elevator? A Software Engineering Perspective on Game Bugs

In the past decade, the complexity of video games have increased dramatically and so have the complexity of software systems behind them. The difficulty in designing and testing games invariably leads to bugs that manifest themselves across funny video reels on graphical glitches and millions of submitted support tickets. This paper presents an analysis of game developers and their teams who have knowingly released bugs to see what factors may motivate them in doing so. It examines different development environments as well as inquiring into varied types of game platforms and play-style. Above all, it seeks out how established research on software development best practices and challenges should inform understanding of these bugs. These findings may lead to targeted efforts to mitigate some of the factors leading to glitches, tailored to the specific needs of the game development team