Balance trucks:Using crowd-sourced data to procedurally-generate gameplay within mobile games

Within the field of procedural content generation (PCG) research, the use of crowd-sensing data has, until now, primarily been used as a means of collecting information and generating feedback relating to player experience within games, and game aesthetics. However, crowd-sensing data can offer much more, supplying a seemingly untapped font of information which may be used within the creation of unique PCG game spaces or content, whilst providing a visible outlet for the dissemination of crowd-sensed material to users. This paper examines one such use of crowd-sensed data, the creation of a game which will reside within the CROWD4ROADS (C4RS) application, SmartRoadSense (SRS). The authors will open with a brief discussion of PCG. Following this, an explanation of the features and aims of the SRS application will be provided. Finally, the paper will introduce ‘Balance Trucks’, the SRS game, discussing the concepts behind using crowd-sensed data within its design, its development and use of PCG

Data-driven design : a case for maximalist game design

Maximalism in art refers to drawing on and combining multiple different sources for art creation, embracing the resulting collisions and heterogeneity. This paper discusses the use of maximalism in game design and particularly in data games, which are games that are generated partly based on open data. Using Data Adventures, a series of generators that create adventure games from data sources such as Wikipedia and Open- StreetMap, as a lens we explore several tradeoffs and issues in maximalist game design. This includes the tension between transformation and fidelity, between decorative and functional content, and legal and ethical issues resulting from this type of generativity. This paper sketches out the design space of maximalist data-driven games, a design space that is mostly unexplored.peer-reviewe

Conception d’un outil de génération procédurale d’environnements urbains destiné à la production de jeu vidéo

Au fil des dernières décennies, l’évolution de la capacité de calculs et de la qualité des outils a permis d’augmenter la qualité visuelle des jeux vidéo. En conséquence, l’effort et le coût nécessaires pour créer ces jeux ont explosé. Il y a donc un besoin concernant la création d’outils afin de permettre aux artistes d’automatiser certaines tâches non-créatives, notamment à ce qui a trait à la génération d’environnement. Ce mémoire a pour objectif de décrire les différentes étapes de la création d’un outil permettant de générer de manière semi-automatique un environnement urbain. Une des contraintes de cette recherche est que cet outil doit pouvoir être utilisé dans un cadre de production de jeu vidéo. Pour cela, l’outil doit répondre à un certain nombre de critères, comme pouvoir laisser l’artiste décider de l’aspect visuel des bâtiments ainsi que du plan du réseau routier pour répondre aux décisions prises par la direction artistique. Ce mémoire fait dans un premier temps un état des lieux des travaux existants dans le domaine de la génération procédurale en milieu de jeu, et plus précisément sur les méthodes de génération procédurale d’environnements urbains. Dans une deuxième partie, ce document présente les différentes étapes de création nécessaires pour obtenir un outil de génération procédurale d’environnements urbains. Enfin, les résultats obtenus avec l’outil en question sont présentés, ouvrant la porte à une discussion sur d’éventuels compléments et travaux futurs. Ce mémoire est accompagné d’une création, un outil de génération procédurale permettant à l’artiste de générer une zone urbaine peuplée de bâtiments paramétrables à partir de modules qu’il aura préalablement créé. During the last decades, the evolution of computation capacity and the quality of tools allows to improve the visual quality of video games. Consequently, effort and cost needed to create such games exploded. There is therefore a need for the creation of tools to allow artists to automate certain non-creative tasks, including those related to environment generation. This master’s thesis aims to describe the different stages of the development of a tool for semiautomatically generating an urban environment. One of the constraints of this research is that this tool must be operational in a context of video game production. To do so, the tool must meet a certain number of criteria, such as being able to let the artist determine the buildings’ visual aspect, or the road network scheme chosen by the artistic direction. Firstly, this master’s thesis analyzes literature reviews about PCG, and precisely urban environment generations. Secondly, this document presents the different steps needed to obtain an urban environment procedural generation tool. Then the results obtained with this tool are shown, leading to a discussion and an opening on potential future works on the subject. This master’s thesis is accompanied by a creation, a procedural generation tool allowing the artist to generate an urban area populated with configurable buildings made from modules built by the artist

3D terrain generation using neural networks

With the increase in computation power, coupled with the advancements in the field in the form of GANs and cGANs, Neural Networks have become an attractive proposition for content generation. This opened opportunities for Procedural Content Generation algorithms (PCG) to tap Neural Networks generative power to create tools that allow developers to remove part of creative and developmental burden imposed throughout the gaming industry, be it from investors looking for a return on their investment and from consumers that want more and better content, fast. This dissertation sets out to develop a PCG mixed-initiative tool, leveraging cGANs, to create authored 3D terrains, allowing users to directly influence the resulting generated content without the need for formal training on terrain generation or complex interactions with the tool to influence the generative output, as opposed to state of the art generative algorithms that only allow for random content generation or are needlessly complex. Testing done to 113 people online, as well as in-person testing done to 30 people, revealed that it is indeed possible to develop a tool that allows users from any level of terrain creation knowledge, and minimal tool training, to easily create a 3D terrain that is more realistic looking than those generated by state-of-the-art solutions such as Perlin Noise.Com o aumento do poder de computação, juntamente com os avanços neste campo na forma de GANs e cGANs, as Redes Neurais tornaram-se numa proposta atrativa para a geração de conteúdos. Graças a estes avanços, abriram-se oportunidades para os algoritmos de Geração de Conteúdos Procedimentais(PCG) explorarem o poder generativo das Redes Neurais para a criação de ferramentas que permitam aos programadores remover parte da carga criativa e de desenvolvimento imposta em toda a indústria dos jogos, seja por parte dos investidores que procuram um retorno do seu investimento ou por parte dos consumidores que querem mais e melhor conteúdo, o mais rápido possível. Esta dissertação pretende desenvolver uma ferramenta de iniciativa mista PCG, alavancando cGANs, para criar terrenos 3D cocriados, permitindo aos utilizadores influenciarem diretamente o conteúdo gerado sem necessidade de terem formação formal sobre a criação de terrenos 3D ou interações complexas com a ferramenta para influenciar a produção generativa, opondo-se assim a algoritmos generativos comummente utilizados, que apenas permitem a geração de conteúdo aleatório ou que são desnecessariamente complexos. Um conjunto de testes feitos a 113 pessoas online e a 30 pessoas presencialmente, revelaram que é de facto possível desenvolver uma ferramenta que permita aos utilizadores, de qualquer nível de conhecimento sobre criação de terrenos, e com uma formação mínima na ferramenta, criar um terreno 3D mais realista do que os terrenos gerados a partir da solução de estado da arte, como o Perlin Noise, e de uma forma fácil

From gamestorming to mobile learning : a conceptual framework and a gaming proposition to explore the design of flourishing business models

Cette démarche de thèse débute par la mise au point d'un cadre conceptuel à propos de la durabilité ('sustainability') et du MA (modèle d'affaires), pour cadrer une recherche sur la définition et la conception de MA durable. Grâce notamment à Ehrenfeld (2005), le MAF (modèle d'affaires pour un avenir florissant ou 'flourishing future') est défini. La question est maintenant de savoir comment introduire les gestionnaires à la théorie et la pratique du MAF? Quelle est la nature de l'effort cognitif exigé? Et l'apprentissage peut-il être stimulé par le 'gamestorming' en proposant un espace d'apprentissage ouvert à la formation de nouveaux concepts. Le premier chapitre présente les origines du MA suite à l'affrontement dans les années 1980 entre la finance d'entreprise et la stratégie d'entreprise lors de la naissance du premier logiciel de tableur. Dès lors, le chapitre un propose d'envisager l'histoire du MA en trois périodes : d'abord le MA pour la valeur numérique, ensuite, le MA architectural et finalement, le MA durable. Mais les académiciens et les praticiens ne s'entendent pas sur la définition de MA durable. Il existe une opposition entre les approches faible et forte. Nous adoptons dans cette thèse la définition et l'engagement d'Ehrenfeld (2005) à un avenir florissant, définissant ainsi le MAF ou modèle d'affaires (pour un avenir) florissant. Le chapitre un montre que le MA pour la valeur numérique implique le calcul comme un mode cognitif, le MA architectural est plus associé à l'interprétation comme mode cognitif, tandis que MAF devrait être conçu grâce à la cognition située et à la macrocognition. Le chapitre deux oppose le MA développé sous une vision cognitive plus traditionnelle de computation-interprétation à la construction du MAF exigeant de nouvelles conditions préalables nécessaires à la cognition située et à la macrocognition. De cette façon, les acteurs conçoivent un MAF via leur interface sensorimotrice où le sens se dégage de multiples interactions avec la matérialité sociale et la matérialité physique du modèle. Aussi un MAF devient un objet public partagé, ouvert au développement de la compétence sociale dans une situation où les principes de macrocognition s'appliquent. Le chapitre trois fait le bilan d'une expérience d'enseignement / apprentissage avec une classe d'étudiants au MBA dans laquelle les étudiants devaient gérer dans le même cours, à la fois le canevas dédié au MA (CMA) et une modélisation organisationnelle plutôt abstraite reliée à la gestion des connaissances (Morabito et al., 1999). Cette expérience d'apprentissage est un cas de conception dense ('thick design') à l'intérieur d'une salle de classe inversée qui permet d'explorer l'idée suivante : si la matérialité sociale et physique fait partie du domaine de conception, les exigences de la cognition et la charge cognitive seront plus lourdes. Le chapitre se termine en associant durabilité faible avec un design mince ('thin') et la durabilité forte avec la conception dense ('thick'). Le chapitre quatre plonge plus profondément dans les questions de durabilité. Ce chapitre présente une expérience jeu avec Logim@s© qui s'est produite dans la division du développement durable d'une grande ville canadienne : les quatre joueurs étaient gestionnaires de développement durable ou professionnels dans le domaine. Le jeu est basé sur le livre de Steven Moore (2007) qui expose les scénarios, les modes logiques et les discours qui permettent à trois villes très différentes (Curitiba, Austin et Francfort) de déployer leur leadership en matière de durabilité. Un défi de conception dense est au cœur de l'expérience : comment un joueur peut-il utiliser l'approche CMA alors que des discours contradictoires risquent de le bloquer cognitivement? Les joueurs sont dans un mode logique inductif / déductif. Vont-ils passer en mode abductif? Le chapitre cinq examine comment le jeu Logim@s© pourrait devenir une plateforme ouverte de gamestorming, appelons-la SustAbd©. Ce chapitre comporte deux parties : la première partie est une réflexion sur le processus de conception de jeu pour justifier une approche plate-forme d'architecture composé du noyau SustAbd© et de sa périphérie, et une seconde partie, où cinq cas d'utilisation UML sont proposés. Le chapitre six s'appuie sur l'expérience du chercheur comme un tuteur humain dans les expériences d'enseignement inversé et de 'gamestorming.' Le but de ce chapitre est d'adopter la modélisation cognitive (MC) comme approche pour remplacer un tuteur humain par un robot 'situé.' Ce chapitre se poursuit avec des développements au sujet du caractère situé des robots. Ces idées permettent de concevoir SustAbdPLAY© conformément au caractère situé et aux conditions de macrocognition propres au design d'un MAF. La modélisation sociale avec iStar permet de clarifier la conception. Le chapitre sept termine la thèse. Il décrit les leçons apprises, les limites de l'étude ainsi que la suggestion de recherches futures. Une conclusion générale clôt le chapitre.\ud ______________________________________________________________________________ \ud MOTS-CLÉS DE L’AUTEUR : Business model, modèle d'affaires, soutenabilité, développement durable, cognition, matérialité, gamestorming, apprentissage mobile, recherche action, desig

Contributions to Big Geospatial Data Rendering and Visualisations

Current geographical information systems lack features and components which are commonly found within rendering and game engines. When combined with computer game technologies, a modern geographical information system capable of advanced rendering and data visualisations are achievable. We have investigated the combination of big geospatial data, and computer game engines for the creation of a modern geographical information system framework capable of visualising densely populated real-world scenes using advanced rendering algorithms. The pipeline imports raw geospatial data in the form of Ordnance Survey data which is provided by the UK government, LiDAR data provided by a private company, and the global open mapping project of OpenStreetMap. The data is combined to produce additional terrain data where data is missing from the high resolution data sources of LiDAR by utilising interpolated Ordnance Survey data. Where data is missing from LiDAR, the same interpolation techniques are also utilised. Once a high resolution terrain data set which is complete in regards to coverage, is generated, sub datasets can be extracted from the LiDAR using OSM boundary data as a perimeter. The boundaries of OSM represent buildings or assets. Data can then be extracted such as the heights of buildings. This data can then be used to update the OSM database. Using a novel adjacency matrix extraction technique, 3D model mesh objects can be generated using both LiDAR and OSM information. The generation of model mesh objects created from OSM data utilises procedural content generation techniques, enabling the generation of GIS based 3D real-world scenes. Although only LiDAR and Ordnance Survey for UK data is available, restricting the generation to the UK borders, using OSM alone, the system is able to procedurally generate any place within the world covered by OSM. In this research, to manage the large amounts of data, a novel scenegraph structure has been generated to spatially separate OSM data according to OS coordinates, splitting the UK into 1kilometer squared tiles, and categorising OSM assets such as buildings, highways, amenities. Once spatially organised, and categorised as an asset of importance, the novel scenegraph allows for data dispersal through an entire scene in real-time. The 3D real-world scenes visualised within the runtime simulator can be manipulated in four main aspects; • Viewing at any angle or location through the use of a 3D and 2D camera system. • Modifying the effects or effect parameters applied to the 3D model mesh objects to visualise user defined data by use of our novel algorithms and unique lighting data-structure effect file with accompanying material interface. • Procedurally generating animations which can be applied to the spatial parameters of objects, or the visual properties of objects. • Applying Indexed Array Shader Function and taking advantage of the novel big geospatial scenegraph structure to exploit better rendering techniques in the context of a modern Geographical Information System, which has not been done, to the best of our knowledge. Combined with a novel scenegraph structure layout, the user can view and manipulate real-world procedurally generated worlds with additional user generated content in a number of unique and unseen ways within the current geographical information system implementations. We evaluate multiple functionalities and aspects of the framework. We evaluate the performance of the system, measuring frame rates with multi sized maps by stress testing means, as well as evaluating the benefits of the novel scenegraph structure for categorising, separating, manoeuvring, and data dispersal. Uniform scaling by n2 of scenegraph nodes which contain no model mesh data, procedurally generated model data, and user generated model data. The experiment compared runtime parameters, and memory consumption. We have compared the technical features of the framework against that of real-world related commercial projects; Google Maps, OSM2World, OSM-3D, OSM-Buildings, OpenStreetMap, ArcGIS, Sustainability Assessment Visualisation and Enhancement (SAVE), and Autonomous Learning Agents for Decentralised Data and Information (ALLADIN). We conclude that when compared to related research, the framework produces data-sets relevant for visualising geospatial assets from the combination of real-world data-sets, capable of being used by a multitude of external game engines, applications, and geographical information systems. The ability to manipulate the production of said data-sets at pre-compile time aids processing speeds for runtime simulation. This ability is provided by the pre-processor. The added benefit is to allow users to manipulate the spatial and visual parameters in a number of varying ways with minimal domain knowledge. The features of creating procedural animations attached to each of the spatial parameters and visual shading parameters allow users to view and encode their own representations of scenes which are unavailable within all of the products stated. Each of the alternative projects have similar features, but none which allow full animation ability of all parameters of an asset; spatially or visually, or both. We also evaluated the framework on the implemented features; implementing the needed algorithms and novelties of the framework as problems arose in the development of the framework. Examples of this is the algorithm for combining the multiple terrain data-sets we have (Ordnance Survey terrain data and Light Detection and Ranging Digital Surface Model data and Digital Terrain Model data), and combining them in a justifiable way to produce maps with no missing data values for further analysis and visualisation. A majority of visualisations are rendered using an Indexed Array Shader Function effect file, structured to create a novel design to encapsulate common rendering effects found in commercial computer games, and apply them to the rendering of real-world assets for a modern geographical information system. Maps of various size, in both dimensions, polygonal density, asset counts, and memory consumption prove successful in relation to real-time rendering parameters i.e. the visualisation of maps do not create a bottleneck for processing. The visualised scenes allow users to view large dense environments which include terrain models within procedural and user generated buildings, highways, amenities, and boundaries. The use of a novel scenegraph structure allows for the fast iteration and search from user defined dynamic queries. The interaction with the framework is allowed through a novel Interactive Visualisation Interface. Utilising the interface, a user can apply procedurally generated animations to both spatial and visual properties to any node or model mesh within the scene. We conclude that the framework has been a success. We have completed what we have set out to develop and create, we have combined multiple data-sets to create improved terrain data-sets for further research and development. We have created a framework which combines the real-world data of Ordnance Survey, LiDAR, and OpenStreetMap, and implemented algorithms to create procedural assets of buildings, highways, terrain, amenities, model meshes, and boundaries. for visualisation, with implemented features which allows users to search and manipulate a city’s worth of data on a per-object basis, or user-defined combinations. The successful framework has been built by the cross domain specialism needed for such a project. We have combined the areas of; computer games technology, engine and framework development, procedural generation techniques and algorithms, use of real-world data-sets, geographical information system development, data-parsing, big-data algorithmic reduction techniques, and visualisation using shader techniques