Teses

One of the least noticeable applications in the area of Procedural Generated Content is in generating narratives. Furthermore, when it tends to be used, it focuses on plot generation. Unfortunately, this results in a disregard for the potential emotional impact that storytelling may bring to table, since that, in many cases, it is the way a narrative is told that results in some sort of emotional resonance for an audience. Through a study of storytelling techniques, together with an analysis of existing narrative-driven PCG systems, and by exploring various manners of emotional evaluation in art, a system was built that takes base narratives as input and, through an emotional model, adds storytelling mechanisms to them, seeking to differentiate and maximize one of two opposite emotional moods: Happy and Dour. These narratives are then played in the Virtual Tutor system. A series of experiments consisting of four different narratives were made to discern if the emotional valence of these was successfully differentiated and maximized.

Gone are the days the content of a game was completely created manually and the gameplay was pre-scripted before the game release. Nowadays an increasing number of games use procedurally generated content to provide engaging gaming experiences. Most of the endless single player games generate content based on the difficulty of the challenges combined with the duration of the current game session, which leads to a similar gameplay experience to every player. In this dissertation, we address the problem of keeping the players engaged in a game for longer periods of time. One way to increase the gameplay experience of a game is to increase the feeling of progression. To solve this problem we propose a progression model that creates content based on the player skill. We theorize that, by providing a progression that is adapted to the player based on the player skill, keeping the variety of the challenges will lead to more engaging gameplay experiences. We propose a progression model for the endless level of the mobile game Smash Time. We believe to have created a progression model that is robust and dynamic enough to be used in different games and that excludes the need of using preset difficulty settings. The results from playtests with users suggest that the developed progression model is able to increase the number and duration of the gameplay experiences and has the potential to increase player immersion, creating more engaging gameplay experiences that may, ultimately, increase the overall lifetime of the game itself.

O objectivo desta tese é criar um jogo para ajudar a ensinar Química Orgânica em Realidade Virtual que adicione maior interactividade ao processo de aprendizagem. A interação com os objectos é um dos focos centrais deste jogo, pois os jogadores manipulam átomos e moléculas no decorrer do jogo inteiro, e para tornar esta interação o mais natural e fácil de utilizar possível, foi decidido utilizar o sensor Leap Motion em conjunto com a tecnologia de Realidade Virtual. Os alunos usam as próprias mãos para interagir com o jogo e existem diferentes métodos que podem ser utilizados, dependendo do objectivo da interação em questão. O jogo consiste em criar moléculas, ligando os átomos uns aos outros, para ultrapassar os desafios que são apresentados e, por consequência, progredir nos níveis. Os desafios são baseados na matéria que é ensinada aos alunos do ensino secundário, especificamente no 10º ano, e as regras relacionadas com a junção dos átomos para criar as moléculas devem ser seguidas. A implementação da interação com objectos foi atingida e todo o desenvolvimento do jogo foi realizado em três iterações. Foram realizada uma avaliação com alunos do ensino secundário, no final da última iteração, para verificar se os objectivos propostos foram atingidos. Esta avaliação consistia em completar o tutorial e o modo de jogo Normal, que foi simplificado, tendo apenas quatro níveis com dois desafios cada. Os resultados foram bastante positivos, mostram que o jogo é divertido, agradável, e que tem potencial para ser usado numa aula.

This work proposes a solution to improve the cooperation between humans and computer Artificial Intelligence (AI), as a colleague, in the creation of puzzles for video game levels. With this interaction we hope to give the designer a source of creative stimulus, in order to achieve overall more creative results than those obtained if said designer was working alone. The proposed solution consists of a co-creative puzzle creation tool, focused on improving creativity by allowing human and computer to work together in producing content using the Legend of Grimrock 2 Level Editor, exploring the digital “peer” paradigm. Its interface can be used by the designer to preview generated suggestions and orient its behavior. Suggestions are generated and iteratively evolved by three genetic algorithms and can be guided by the designer on different domains: objective, innovation, user map; all then combined in a fourth one that re-evaluates the best suggestions of each previous algorithm, again on the three domains, with different weights based on the users configuration, to choose the best suggestion overall. Results showed a positive influence on the puzzle creation because our approach takes into account the smaller nuances of the co-creative interaction. Outlined improvements such as a better way to support designer-specific interaction patterns, improved algorithm behaviour and integration with past tools set the direction for future work. We concluded that through an intuitive interface, flexible and adjustable behavior, we were able to provide some positive contributions to the quality of the co-creative puzzle creation process.