Fei Fang

Talk Title: Game Theory and Machine Learning for Addressing Societal Challenges: From Theory to Real-World Impact

Talk Abstract:
Societal challenges spanning security, environmental sustainability, food security, and transportation often involve complex decision-making by multiple self-interested agents. In our research, we delve into the development of game theory and machine learning-based methodologies and tools to tackle these challenges, with a strong focus on contributing to the social good.
In this talk, I will introduce our work that has led to successful applications in ferry protection, environmental conservation, and food rescue. Moreover, I will cover our foundational research in inverse game theory, scalable game solving, and interpretable multi-agent reinforcement learning. These advancements are motivated by the real-world problems we have been working on and enable us to tackle more complex decision-making scenarios in the future.