Group items tagged

"Driven by an initiative of the Adult & Paediatric Diabetes Psychology Service of New Zealand, research has been performed to develop new mechanisms, in the form of computer games, to educate children and teenagers about living with diabetes. Aimed at achieving maximum education effectiveness, the ultimate goal of our research is to develop innovative machine learning algorithms that can be used in games to improve their ability to learn about the changing needs of children and to incorporate this intelligence into the game interface. We also plan to collect and report on the information collected from testing our computer games within a small group of children who have been diagnosed with type I diabetics. "

"In this thesis we present the design and evaluation of a learning game based on the concept of 'stealth learning' and the theory of constructivism, which provides an early introduction to basic programming concepts and procedural literacy to children from 10 years upwards, attempting to provide the highest possible degree of immersion. The evaluation involves a number of tests verifying usability, immersion and motivation, and an attempt to test the transferability of the ingame acquired knowledge to reading pseudocode, the results of which, triggered further reflection on the possibility of adding new layers of complexity and embedding evaluation of learning within the game experience."

Abstract: "Herein is proposed the creation of an Application Program- ming Interface (API) for the Unity 3 and 4 video game de- velopment engine that not only reads behavioral measures from traditional video game input devices (such as if there has been an increase in mouse movements and clicks) but also takes into account physiological measures from biomet- ric devices (such as an increase in respiratory rate). The API parses these inputs based on study results that correlated player performance and engagement with physio- logical signs across several dierent game genres. Through the use of several rudimentary machine learning algorithms, raw physiological data is transformed into data relevant to a developer, including player engagement. The results of these calculations allow a game designer to have powerful tools for detecting when players experience certain emotions, and al- low for the design of aective games. Furthermore, the API also exposes the raw data to de- velopers wishing to propose and utilize their own learning algorithms, to allow for a rich development environment for developers of all skill levels. These development tools will enrich the game experience for the player, as well as prepare designers for the use of the next wave of non-traditional in- put hardware. This report serves to illustrate the current status of the API. A brief overview of the signicance of galvonic skin re- sponse (GSR), heart rate (HR), and respiratory rate (RR) in detecting player performance and engagement will be fol- lowed by a discussion of the API itself and the design choices therein."

"This paper focuses on the design and development of a gamebased forensics course using the game-based learning (GBL) approach building the game in a real computing environment that has direct access to actual forensics tools from a forensics machine and the evidence from a suspect machine. Interactive visualizations will be used to help students to understand the intangible and inaccessible abstract concepts such as deleted/hidden/encrypted/over-written digital evidence."

Abstract: "Video games that customize to a player's experience level and abilities have the potential to allow a broader range of players to become engaged and maintain interest as they progress in experience level. A game that uniquely customizes the player's experience could attract additional demographics to gaming, which will result in a distinct edge in marketability and potential revenue. This thesis examines a subsection of adaptive gaming systems from the perspective of identifying game factors that alter the level of difficulty. Our focus is to provide a solution useful to both research and commercial gaming communities by developing a system that simulates results offline yet can be integrated into online play. While online performance is the main goal of an adaptive system, the offline simulation provides several benefits. Offline simulation allows the elimination of insignificant factors from inclusion in the training and evolution phase of machine learning algorithms. In addition it provides commercial games with a useful tool or method for performing game balancing and level tuning. To test our approach we designed a test-bed version of the game Pac-Man. The experimental testbed alters environment variables to evaluate their effect on a set of selected response variables. Observing the results of several response variables provides the potential to represent multiple player states, though our focus is on controlling the difficulty for a player. The testbed will simulate the actions of both Pac-Man and the ghosts over a variety of different settings and strategies. The evaluation of a factor's significance and its effect size are calculated using a factorial analysis approach. This method allows the identification of factors relevant to both individual strategies, and the set of all player strategies. Finally, as a proof of concept for both the online and adaptation prospects of this method, we developed a prototype adaptive system. Utilizing the releva

"MACHS, a platform for the generation of serious games, i.e. courses in 3D environments for machine-tool training. The platform consists of two applications: an easy-to-use authoring tool for editing the courses and a 3D simulator for running them."

Abstract: "Game Artificial Intelligence (Game AI) is a subdiscipline of Artificial Intelligence (AI) and Machine Learning (ML) that explores the ways in which AI and ML can augment player experiences in computer games. Storytelling is an integral part of many modern computer games; within games stories create context, motivate the player, and move the action forward. Interactive Narrative is the use of AI to create and manage stories within games, creating the perception that the player is a character in a dynamically unfolding and responsive story. This paper introduces Game AI and focuses on the open research problems of Interactive Narrative."

Description in Google Books: "The Video Game Industry provides a platform for the research on the video game industry to draw a coherent and informative picture of this industry. Previously this has been done sparsely through conference papers, research articles, and popular science books. Although the study of this industry is still stigmatized as frivolous and 'only' game oriented, those who grew up with video games are changing things, especially research agendas, the acceptance of studies, and their interpretation. This book describes and defines video games as their own special medium. They are not pinball from which they grew, nor movies which they sometimes resemble. They are a unique form of entertainment based on meaningful interactions between individuals and machine across a growing sector of the population. The Video Game Industry provides a reference foundation for individuals seriously interested in the industry at the academic level. As a result, this book will serve as a reference in curricula associated with video game development for years to come. "