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Algorithmic game theory offers vital tools for fair decision-making and efficient resource allocation in complex systems.
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.
The course teaches students the basics and recent advancement in Algorithmic Game Theory, specifically in computational social choice and fair resource allocation.
22 July — 26 July 2024
City University of Hong Kong , Academic Exchange Building, AE-040
HK$3,000 (Includes accommodation)
Apply by 23 June 2024
Fully booked
Past
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.
Doctoral students and early career researchers.
If you have any enquiries about the course, please contact Zifan Gong by email at zifangong2-c@my.cityu.edu.hk.
Professor, Department of Computer Science, City University of Hong Kong
Assistant Professor, School of Computing, University of Nebraska-Lincoln
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