The need for research in algorithmic game theory is evident in the increasingly interconnected and diverse world we live in. As societies become more complex, capturing and aggregating collective preferences accurately is crucial for fair and representative decision-making. Simultaneously, the efficient allocation of limited resources is of paramount importance in various sectors, including healthcare, education, transportation, and environmental management.
The importance of this research lies in its potential to provide practical solutions to these pressing challenges.
What you'll study
Advanced models, algorithms, and mechanisms that optimise resource allocation, minimise inefficiencies, and satisfy fairness criteria by integrating concepts from social choice theory and mechanism design. The outcomes of these will inform evidence-based decision-making for equitable and efficient resource allocation. The course adopts an applied approach that combines theoretical insights with empirical analysis and real-world case studies to validate and refine the proposed models and mechanisms.
Who is the course for
Doctoral students and early career researchers.
Course director
Professor, Department of Computer Science, City University of Hong Kong
Course co-director
Assistant Professor, School of Computing, University of Nebraska-Lincoln