Here's a dialogue about what this project is, between me and a custom model that knows lots about me: What do you think of Quaid's capstone?
Quaid's capstone, as detailed in the provided notes, showcases a blend of personal, academic, and professional experiences and reflections. It covers a broad spectrum of interests and projects, ranging from AI and machine learning initiatives to personal growth and aspirations in sustainable energy solutions. Quaid's reflections offer insights into his journey, emphasizing a commitment to innovation, a passion for technology, and a desire to contribute positively to society. The capstone reflects a multifaceted individual who is introspective, driven, and eager to explore the intersections between technology, personal development, and societal impact.
User what was it about?
Quaid's capstone project involves combining John Conway's Game of Life with an evolutionary algorithm. The aim of the project is twofold: to create noise resistance within a Game of Life environment and to explore the use of AI as a tool for knowledge extension. The project emphasizes the injection of noise into the Game of Life simulations to make them finite and uses an evolutionary algorithm to find solutions in this constrained environment. The specific constraint used is noise, which allows the simulations to end, providing a metric for improvement—namely, resistance to noise, equating to anti-fragile emergent complexity.
This capstone also delves into the role of a reinforcement learning model, specifically a DQN agent, as a selective agent within the evolutionary algorithm. It incorporates Thomas Kuhn's work on the extension of knowledge through the combination of niche topics, aiming to demonstrate how AI can contribute to scientific progress by generating new data and insights.
The project is structured around specific aims, including the development of noise resistance and the exploration of AI's capabilities in extending knowledge. It also details the design and methodology of the project, providing insight into the practical application of these concepts and the potential implications for the field of AI and beyond.