Master in Artificial Intelligence / Μεταπτυχιακό στην Τεχνητή Νοημοσύνη

This research explores the optimization of Evolutionary Algorithms (EAs) using Unity Job System, a framework enabling task parallelization across multiple CPU threads. EAs, widely applied in optimization and artificial intelligence, often face performance bottlenecks due to their computational intensity, especially in real-time or resource-constrained environments such as game development. By leveraging Unity's parallelization capabilities, the study aims to enhance the performance of EAs while addressing their computational challenges. A custom Unity application was developed to compare the performance of EA components - including fitness functions, selection, crossover, and mutation - under single-threaded and multi-threaded implementations. Tests were conducted on functions with varying computational complexities, including Big-O synthetic functions and benchmark functions such as Rastrigin and Rosenbrock. Additional evaluations included the Traveling Salesman Problem and the efficiency of core EA operations. The results demonstrate the potential for significant performance improvements when using Unity's Parallel Job System, particularly for tasks involving extensive data processing. However, limitations such as platform constraints, data preparation overhead, and restricted debugging capabilities are noted. This study provides practical insights for developers and researchers aiming to integrate parallel computing into real-time applications and highlights the potential of Unity as a versatile platform for advancing artificial intelligence in game development.

This thesis explores the Voronoi game, a strategic competition model that combines principles from game theory and computational geometry. In the Voronoi game, players are placed within a bounded space, and territory is determined by proximity, forming regions called Voronoi cells. The objective is to capture the maximum area within these cells, leading to complex strategic behaviors. This study investigates the core mechanics, variations, and applications of the Voronoi game, as well as its implications for broader fields such as network design, facility location, and competitive spatial strategies. Through analytical and computational approaches, we characterize equilibria, evaluate player strategies, and explore multi-round dynamics, providing a comprehensive understanding of the games mathematical and practical relevance.

This thesis explores autonomous navigation of Unmanned Aerial Vehicles (UAVs) and a land rover in GPS-denied environments through the integration of SLAM and reinforcement learning techniques. RTAB-Map SLAM is used to create real-time 3D maps, explore lite for autonomous exploration and navigation algorithms for safely navigating the UAV to the target location. The UAV also employs Deep Q-Network (DQN) for discrete action navigation. Additionally, a Twin Delayed Deep Deterministic Policy Gradient (TD3) network is implemented for the land rover, allowing continuous action control. Both systems utilize RGB-D cameras and LiDAR sensors for environmental perception, obstacle avoidance and localization. The performance of these systems is evaluated in simulation.

In a world where personal data can easily be extracted from the simplest of online transactions or actions in general, the need for sufficient data protection protocols, laws and regulations has never been more dire. In past years, the internet was at its infancy which led countries to adapt or establish laws that did not really protect the personal data of its residents from internet attacks, scams etc. The rapid growth of the internet has led countries to expand on their previous laws and regulations or to create new ones. The differences of these laws and regulations is the main scope of this thesis. This thesis will begin with an overview of the previous law in Europe (Data Protection Directive) and will continue with an overview of the law that replaced the DPD, the General Data Protection Regulation while providing a comparison between the two laws. The thesis then will move on with the different state laws in the United States. In both the overview of the European laws and the one of the United States, the format will be the same with minimal to no divergence. There will be some introductory remarks about the law such as the date it was signed into law and then we will list the rights of the data subjects who are subject to this law. We will finish each law by listing the responsibilities and obligations of the controller towards the data subjects. The final part of this thesis will concern the differences between European and US data protection laws and regulations. These differences range from cultural differences regarding who these laws favor most to whether these laws are consent based or not to technical differences such as range of application, lawful basis etc.

The issue at hand is the comprehension of race bias and gender selection in the data analysis domain of Technical Intelligence, which is the subject of the original problem analysis in this thesis. We identify the flaws that contribute to bias in Technical Intelligence and assess the repercussions of bias on systems and society. Opportunity and challenge are both apparent and identifiable in the realm of research as a result of technical intelligence