Profiling Players Through In-Game Animations
Current data collection methods for video-games focus on specific events or complete recordings of the gameplay sessions. The purpose of this thesis is to provide a novel method of data collection in video-games, specifically the utilisation of animation data for recording and categorising player behaviour. This alternate method is meant to be fast, with low overhead on the machine that runs it. Through this work, we conclude that animation collection is a beneficial method for data collection, and that it can be applied to future games through the development of an add-on for popular game engines.
Mixed Procedurally Generated Creatures
Animations are a core component of video games. Animations typically require dedicated animators and are relatively inflexible, making it extremely difficult to animate a character without enforcing strict restrictions on the virtual world where it is placed. We propose a framework to explore the procedural generation of animations in arbitrary tridimensional virtual worlds, by using neuroevolution to create and evolve neural networks that output forces at a creature’s skeleton joints in order to produce motion and movement that are credible and physically coherent with the virtual world topology and the creature's state. Evaluation was done by selecting tasks for which our framework was able to generate animations that are different between each other but that achieve the same result proving that neuroevolution can offer different solutions to animation problems even when using different body topologies which were also able to achieve the same task using the same fitness method.
Application of RRT for overtaking in a Racing Car Simulation
This document describes the application and development of a TORCS robot that, on a racing scenario, follows a determined trajectory (referred as racing line) calculated with the K1999 algorithm and, in case of overtaking, one that is traced by a Rapidly-exploring Random Tree based algorithm called Adapt and Overtake-RRT (ADOVER for short), working in two different modes that will later be compared. It is meant to compete against other robots and also humans, having as a requirement maintaining an acceptable performance throughout its execution. After some testing with static opponents, the robot was unable to perform the desired task. On the other hand, it showed promising results in terms of speed and efficiency. Possible improvements are discussed in the last segment.
Virtual Reality Football Videogame - A Social Experience
A tecnologia está sempre em constante evolução, e a indústria dos jogos não é excepção. Os últimos desenvolvimentos têm sido na área da Realidade Virtual (RV), com algumas das maiores empresas do mundo a desenvolverem hardware bastante capaz, mas os maiores estúdios de desenvolvimento de jogos não têm acompanhado esses passos. Os jogos de RV têm o potencial de elevar o nível dos jogos para um outro patamar, colocando o jogador no centro do mundo virtual do jogo, abrindo portas a uma infinidade de possibilidades a serem exploradas pela criatividade de desenvolvedores. No entanto, com a RV os utilizadores também se podem sentir isolados das pessoas e do mundo real à sua volta, ganhando as experiências de RV partilhadas um importante papel no sucesso da RV. De forma a perceber melhor os desafios inerentes à criação de conteúdo em RV, propomos o desenvolvimento de um jogo em RV que deverá ser jogado por duas pessoas salientando a necessidade de explorar a RV como um modo de interacção e comunicação, ao invés de ser uma experiência isolada. O jogo consiste num jogo de futebol, em que os jogadores se defrontam. Não é suposto ser um jogo no qual os jogadores andem pelo campo inteiro; em vez disso, cada jogador está na sua respectiva baliza, rematando a bola para marcar golos, tentando defender os remates do adversário. Tornando este jogo numa experiência partilhada, pretendemos criar e fortalecer laços entre pessoas através de um método tão propício a isso, que é o divertimento.