An Algorithmic Theory of Markets and Their Application to Decentralized Markets
DOI:
https://doi.org/10.1609/aaai.v36i11.21576Keywords:
Market Equilibrium, Equilibrium Computation, Learning In Games, Optimization AlgorithmsAbstract
Broadly speaking, I hope to dedicate my PhD to improving our understanding of algorithmic economics with the ultimate goal of building welfare improving decentralized technology for markets. In the following pages, I describe how my past work has built on the existing literature to get closer to the goal of creating such technologies, and describe what research paths this work opens up for the rest of my PhD. I believe that my research has the potential to provide algorithmic solutions to problems in machine learning, optimization, and game theory, and can be used to improve the efficiency of online marketplaces.Downloads
Published
2022-06-28
How to Cite
Goktas, D. (2022). An Algorithmic Theory of Markets and Their Application to Decentralized Markets. Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 12878-12879. https://doi.org/10.1609/aaai.v36i11.21576
Issue
Section
The Twenty - Seventh AAAI / SIGAI Doctoral Consortium