Kokulan Thangasuthan

My project is focused on constructing a dynamic, relationship-based knowledge graph. This graph intricately maps interactions and dependencies among various entities such as agents, objects, and subjects within a specific environment. A distinctive feature of this project is its ability to identify and integrate hidden subjects into the knowledge graph, enabling it to evolve as new data or entities are introduced. Central to this research is the application of game theory to create multiple simulations, around five in total, each projecting potential outcomes contingent on the actions of agents within the system. These simulations are crucial for envisioning various future scenarios and understanding the range of possible developments. Further enhancing the project's robustness is the use of model checking tools, like Rational Verification, to conduct probabilistic verification. This process is designed to identify the most viable simulations with high success probability. The overarching aim is to leverage these insights for improved decision-making and adaptive learning, enabling systems to refine their strategies in response to the dynamic changes in the environment. This project not only seeks to contribute significant advancements to the fields of game theory and adaptive learning but also aims to provide innovative methods for handling uncertainty and complexity in diverse settings.