Game Based

Game-based approaches are increasingly used to evaluate and improve artificial intelligence, particularly large language models (LLMs). Current research focuses on using simple grid-based games like Tic-Tac-Toe to benchmark LLMs' strategic reasoning and rule comprehension, as well as applying game theory frameworks to address challenges in areas like privacy in machine learning and multi-agent coordination (e.g., for UAV path planning). These methods offer rigorous, quantifiable assessments of AI capabilities and provide insights into designing more robust and ethical AI systems, with implications for various fields including web development and cybersecurity.