ADAPTECC: A Role-Play Game about Adapting to Climate Change

The ADAPTECC Climate Change Adaptation Game is a role-play game designed to enable players to experience the difficulties that arise at local and regional levels when authorities have to implement adaptation measures. Adaptation means anticipating the advert effects of climate change (CC) and taking measures to prevent and minimise the damage caused by its impacts. Each player takes the role of the mayor or a councillor of a town affected by CC who must decide what adaptation strategies and measures to take, or of a member of the Regional Environment Department which must distribute funding for adaptation among the various towns. At the end of the game, players should have a greater understanding of the challenges posed by adaptation to CC

Blue Marlin, Makaira nigricans, Movements in the Western North Atlantic Ocean: Results of a Cooperative Game Fish Tagging Program, 1954-88

Blue marlin, Makaira nigricans, tag and recapture data are summarized for 1954-1988. During this period, 8,447 fish have been tagged and only 30 (0.35 percent) have been returned. Results of the tagging program indicate that blue marlin not only travel considerable distances (7,OOO km from the U. S. Virgin Islands to the Ivory Coast of West Africa), but have remained at large for up to 8 years. Seasonal movements, however, are difficult to determine accurately.

A reason for unreason: returns-based beliefs in game theory

Players cooperate in experiments more than game theory would predict. We introduce the ‘returns-based beliefs’ approach: the expected returns of a particular strategy in proportion to total expected returns of all strategies. Using a decision analytic solution concept, Luce’s (1959) probabilistic choice model, and ‘hyperpriors’ for ambiguity in players’ cooperability, our approach explains empirical observations in various classes of games including the Prisoner’s and Traveler’s Dilemmas. Testing the closeness of fit of our model on Selten and Chmura (2008) data for completely mixed 2 × 2 games shows that with loss aversion, returns-based beliefs explain the data better than other equilibrium concepts.

Project Sanitarium: gaming TB: a serious game for a serious problem

Collaborative projects between Industry and Academia provide excellent opportunities for learning. Throughout the academic year 2014-2015 undergraduates from the School of Arts, Media and Computer Games at Abertay University worked with academics from the Infection Group at the University of St Andrews and industry partners Microsoft and DeltaDNA. The result was a serious game prototype that utilized game design techniques and technology to demystify and educate players about the diagnosis and treatment of one of the world's oldest and deadliest diseases, Tuberculosis (TB). Project Sanitarium is a game incorporating a mathematical model that is based on data from real-world drug trials. This paper discusses the project design and development, demonstrating how the project builds on the successful collaborative pedagogical model developed by academic staff at Abertay University. The aim of the model is to provide undergraduates with workplace simulation, wider industry collaboration and access to academic expertise to solve challenging and complex problems.

Mental hoop diaries: emotional memories of a college basketball game in rival fans.

The rivalry between the men's basketball teams of Duke University and the University of North Carolina-Chapel Hill (UNC) is one of the most storied traditions in college sports. A subculture of students at each university form social bonds with fellow fans, develop expertise in college basketball rules, team statistics, and individual players, and self-identify as a member of a fan group. The present study capitalized on the high personal investment of these fans and the strong affective tenor of a Duke-UNC basketball game to examine the neural correlates of emotional memory retrieval for a complex sporting event. Male fans watched a competitive, archived game in a social setting. During a subsequent functional magnetic resonance imaging session, participants viewed video clips depicting individual plays of the game that ended with the ball being released toward the basket. For each play, participants recalled whether or not the shot went into the basket. Hemodynamic signal changes time locked to correct memory decisions were analyzed as a function of emotional intensity and valence, according to the fan's perspective. Results showed intensity-modulated retrieval activity in midline cortical structures, sensorimotor cortex, the striatum, and the medial temporal lobe, including the amygdala. Positively valent memories specifically recruited processing in dorsal frontoparietal regions, and additional activity in the insula and medial temporal lobe for positively valent shots recalled with high confidence. This novel paradigm reveals how brain regions implicated in emotion, memory retrieval, visuomotor imagery, and social cognition contribute to the recollection of specific plays in the mind of a sports fan.

Design of Scheduling Algorithms Using Game Theoretic Ideas

Scheduling a set of jobs over a collection of machines to optimize a certain quality-of-service measure is one of the most important research topics in both computer science theory and practice. In this thesis, we design algorithms that optimize {\em flow-time} (or delay) of jobs for scheduling problems that arise in a wide range of applications. We consider the classical model of unrelated machine scheduling and resolve several long standing open problems; we introduce new models that capture the novel algorithmic challenges in scheduling jobs in data centers or large clusters; we study the effect of selfish behavior in distributed and decentralized environments; we design algorithms that strive to balance the energy consumption and performance.

The technically interesting aspect of our work is the surprising connections we establish between approximation and online algorithms, economics, game theory, and queuing theory. It is the interplay of ideas from these different areas that lies at the heart of most of the algorithms presented in this thesis.

The main contributions of the thesis can be placed in one of the following categories.

1. Classical Unrelated Machine Scheduling: We give the first polygorithmic approximation algorithms for minimizing the average flow-time and minimizing the maximum flow-time in the offline setting. In the online and non-clairvoyant setting, we design the first non-clairvoyant algorithm for minimizing the weighted flow-time in the resource augmentation model. Our work introduces iterated rounding technique for the offline flow-time optimization, and gives the first framework to analyze non-clairvoyant algorithms for unrelated machines.

2. Polytope Scheduling Problem: To capture the multidimensional nature of the scheduling problems that arise in practice, we introduce Polytope Scheduling Problem (\psp). The \psp problem generalizes almost all classical scheduling models, and also captures hitherto unstudied scheduling problems such as routing multi-commodity flows, routing multicast (video-on-demand) trees, and multi-dimensional resource allocation. We design several competitive algorithms for the \psp problem and its variants for the objectives of minimizing the flow-time and completion time. Our work establishes many interesting connections between scheduling and market equilibrium concepts, fairness and non-clairvoyant scheduling, and queuing theoretic notion of stability and resource augmentation analysis.

3. Energy Efficient Scheduling: We give the first non-clairvoyant algorithm for minimizing the total flow-time + energy in the online and resource augmentation model for the most general setting of unrelated machines.

4. Selfish Scheduling: We study the effect of selfish behavior in scheduling and routing problems. We define a fairness index for scheduling policies called {\em bounded stretch}, and show that for the objective of minimizing the average (weighted) completion time, policies with small stretch lead to equilibrium outcomes with small price of anarchy. Our work gives the first linear/ convex programming duality based framework to bound the price of anarchy for general equilibrium concepts such as coarse correlated equilibrium.

A Video Game-Integrated Electromyography Biofeedback Device for Use in Physical Therapy

We present a novel system to be used in the rehabilitation of patients with forearm injuries. The system uses surface electromyography (sEMG) recordings from a wireless sleeve to control video games designed to provide engaging biofeedback to the user. An integrated hardware/software system uses a neural net to classify the signals from a user’s muscles as they perform one of a number of common forearm physical therapy exercises. These classifications are used as input for a suite of video games that have been custom-designed to hold the patient’s attention and decrease the risk of noncompliance with the physical therapy regimen necessary to regain full function in the injured limb. The data is transmitted wirelessly from the on-sleeve board to a laptop computer using a custom-designed signal-processing algorithm that filters and compresses the data prior to transmission. We believe that this system has the potential to significantly improve the patient experience and efficacy of physical therapy using biofeedback that leverages the compelling nature of video games.

Adapting Behavioral Parent Training as an Interactive Computer Game

Behavioral Parent Training (BPT) is a well-established therapy that reduces child externalized behaviors and parent stress. Although BPT was originally developed for parents of children with defiant behaviors, the program’s key concepts are relevant to parenting all children. Since parents might not fully utilize BPT due to cost and program location, we created an online game as a low-cost, easily accessible alternative or complement to BPT. We tested the game with nineteen undergraduate students at the University of Maryland. The experimental group completed pretest survey on core BPT knowledge, played the game, and completed a BPT posttest, while the control group completed a pretest and posttest survey over a three week period. Participants in the experimental group also completed a survey to indicate their satisfaction with the overall program. The experimental group demonstrated significantly higher levels of BPT knowledge than the control group and high levels of satisfaction. This suggests that an interactive, online BPT platform is an engaging and accessible way for parents to learn key concepts.

Making sense of game based user data: learning analytics in applied games

Digital learning games are useful educational tools with high motivational potential. With the application of games for instruction there comes the need of acknowledging learning game experiences also in the context of educational assessment. Learning analytics provides new opportunities for supporting assessment in and of educational games. We give an overview of current learning analytics methods in this field and reflect on existing challenges. An approach of providing reusable software assets for interaction assessment and evaluation in games is presented. This is part of a broader initiative of making available advanced methodologies and tools for supporting applied game development.

What serious game studios want from ICT research: identifying developers’ needs

Although many scholars recognise the great potential of games for teaching and learning, the EU-based industry for such “serious” games” is highly fragmented and its growth figures remain well behind those of the leisure game market. Serious gaming has been designated as a priority area by the European Commission in its Horizon 2020 Framework Programme for Research and Innovation. The RAGE project, which is funded as part of the Horizon 2020 Programme, is a technology-driven research and innovation project that will make available a series of self-contained gaming software modules that support game studios in the development of serious games. As game studios are a critical factor in the uptake of serious games, the RAGE projects will base its work on their views and needs as to achieve maximum impact. This paper presents the results of a survey among European game studios about their development related needs and expectations. The survey is aimed at identifying a baseline reference for successfully supporting game studios with advanced ICTs for serious games.

Seeker: A Serious Game for Improving Cognitive Abilities

Toma, I., Dascalu, M., & Trausan-Matu, S. (2015). Seeker: A Serious Game for Improving cognitive Abilities. In 14th IEEE Int. Conf. RoEduNet (pp. 73–79). Craiova, Romania: IEEE.

Hybrid cluster state proposal for a quantum game

We propose an experimental implementation of a quantum game algorithm in a hybrid scheme combining the quantum circuit approach and the cluster state model. An economical cluster configuration is suggested to embody a quantum version of the Prisoners' Dilemma. Our proposal is shown to be within the experimental state of the art and can be realized with existing technology. The effects of relevant experimental imperfections are also carefully examined.