This thesis explores the potential for software to act as an educational experience for engineers who are learning system dynamics and controls. The specific focus is a spring-mass-damper system. First, a brief introduction of the spring-mass-damper system is given, followed by a review of the background and prior work concerning this topic. Then, the methodology and main approaches of the system are explained, as well as a more technical overview of the program. Lastly, a conclusion and discussion of potential future work is covered. The project was found to be useful by several engineers who tested it. While there is still plenty of functionality to add, it is a promising first attempt at teaching engineers through software development.
The goal of this thesis project was to develop a digital, quantitative assessment of executive functioning skills and problem solving abilities. This assessment was intended to serve as a relative measure of executive functions and problem solving abilities rather than a diagnosis; the main purpose was to identify areas for improvement and provide individuals with an understanding of their current ability levels. To achieve this goal, we developed a web-based assessment through Unity that used gamelike modifications of Flanker, Antisaccade, Embedded Images, Raven’s Matrices, and Color / Order Memory tasks. Participants were invited to access the assessment at www.ExecutiveFunctionLevel.com to complete the assessment and their results were analyzed. The findings of this project indicate that these tasks accurately represent executive functioning skills, the Flanker Effect is present in the collected data, and there is a notable correlation between each of the REFLEX challenges. In conclusion, we successfully developed a short, gamelike, online assessment of executive functioning and problem solving abilities. Future developments of REFLEX could look into immediate scoring, developing a mobile application, and externally validating the results.
Procedural content generation refers to the creation of data algorithmically using controlled randomness. These algorithms can be used to generate complex environments and geological formations as opposed to manually creating environments, using photogrammetry, or other means. Geological formations and the surrounding terrain can be created using noise based algorithms such as Perlin noise. However, interpreting noise in this manner has a number of challenges due to the pseudo-random nature of noise. We will discuss how to generate noise, how to render noise, and the challenges in interpreting noise.
This thesis is based on bringing together three different components: non-Euclidean geometric worlds, virtual reality, and environmental puzzles in video games. While all three exist in their own right in the world of video games, as well as combined in pairs, there are virtually no examples of all three together. Non-Euclidean environmental puzzle games have existed for around 10 years in various forms, short environmental puzzle games in virtual reality have come into existence in around the past five years, and non-Euclidean virtual reality exists mainly as non-video game short demos from the past few years. This project seeks to be able to bring these components together to create a proof of concept for how a game like this should function, particularly the integration of non-Euclidean virtual reality in the context of a video game. To do this, a Unity package which uses a custom system for creating worlds in a non-Euclidean way rather than Unity’s built-in components such as for transforms, collisions, and rendering was used. This was used in conjunction with the SteamVR implementation with Unity to create a cohesive and immersive player experience.
The goal of this thesis project was to develop a digital, quantitative assessment of executive functioning skills and problem solving abilities. This assessment was intended to serve as a relative measure of executive functions and problem solving abilities rather than a diagnosis; the main purpose was to identify areas for improvement and provide individuals with an understanding of their current ability levels. To achieve this goal, we developed a web-based assessment through Unity that used gamelike modifications of Flanker, Antisaccade, Embedded Images, Raven’s Matrices, and Color / Order Memory tasks. Participants were invited to access the assessment at www.ExecutiveFunctionLevel.com to complete the assessment and their results were analyzed. The findings of this project indicate that these tasks accurately represent executive functioning skills, the Flanker Effect is present in the collected data, and there is a notable correlation between each of the REFLEX challenges. In conclusion, we successfully developed a short, gamelike, online assessment of executive functioning and problem solving abilities. Future developments of REFLEX could look into immediate scoring, developing a mobile application, and externally validating the results.
Designing these agents to cover every case of human interaction is difficult, and usually
imperfect, as human players are capable of learning to overcome these agents in unintended
ways. Artificial intelligence is a growing field that seeks to solve problems by simulating
learning in specific environments. The aim of this paper is to explore the applications that the
self play learning branch of artificial intelligence may pose on game development in the future,
and to attempt to implement a working version of a self play agent learning to play a Pokemon
battle. Originally designed Pokemon battle behavior is often suboptimal, getting stuck making
ineffective or incorrect choices, so training a self play model to learn the strategy and structure of
Pokemon battles from a clean slate would result in an organic agent that would outperform the
original behavior of the computer controlled agents. Though unsuccessful in my implementation,
this paper serves as a record of the exploration of this field, and a log of what worked and what
did not, in order to benefit any future person interested in the same topics.
