Bora Yongacoglu

I am an applied mathematician who specializes in multi-agent systems and game theory. (New, as of August 2025) I have moved to industry, where I am currently working on ad auctions at Yelp. This website is an archive of my academic research projects, including some projects that have not yet been published.

I received my PhD from Queen’s University under the supervision of Serdar Yüksel and Gürdal Arslan (University of Hawaii). After Queen’s, I had the pleasure of doing postdoctoral fellowships at the University of Toronto, where I was mentored by Lacra Pavel, and at Mila, where I was mentored by Gauthier Gidel.

Current Interests:

• learning in games
• multi-agent reinforcement learning
• large-scale auctions
• mechanism design for online auctions

For a complete list of papers and preprints, please check out my publications page.

News:

• (August 2025) I’ve joined Yelp as an applied scientist focusing on ad auctions!
• (July 2025) Our paper “Unsynchronized Decentralized Q-Learning: Two Timescale Analysis By Persistence” has been published in SIAM Journal on Control and Optimization!
• (May 2025) I’ve moved to Montreal!
• (October 2024) Our paper “Mean-Field Games With Finitely Many Players: Independent Learning and Subjectivity” was accepted for publication in the Journal of Machine Learning Research!
• (September 2024) Our paper on mathematical structure relevant to learning in multi-agent systems, “Paths to Equilibrium in Games”, was accepted to NeurIPS 2024. See you in Vancouver!
• (July 2024) Our paper “Generalizing Better Response Paths and Weakly Acyclic Games” was accepted for publication at this year’s Conference on Decision and Control in Milan, Italy!
• (April 2024) I delivered a talk in the Machine Learning and Mean Field Games seminar series. A recording is available on YouTube.
• (March 2024) My co-authors and I have written two new papers on game theory, and their pre-prints are now available on arXiv: link to paper 1; link to paper 2. These papers explore how the idea of “satisficing” appears in multi-agent reinforcement learning.
• (December 2023) I travelled to Singapore to present work on asynchronous decentralized Q-learning at the 2023 Conference on Decision and Control.
• (December 2023) I presented some results on $n$-player mean-field games at the Canadian Mathematics Society Winter Meeting in Montreal.
• Our paper “Independent Learning and Subjectivity in Mean-Field Games” has been awarded an Outstanding Student Paper Prize by the 2023 Networks and Communication Systems Technical Committee!
• (May 2023) I gave a talk on learning in stochastic and mean-field games at 9th Meeting on System and Control Theory in Waterloo.
• Our paper on the structure and algorithmic consequences of $\epsilon$-satisficing paths in stochastic games was accepted for publication to SIAM Journal on Mathematics of Data Science.
• (February 2023) I delivered a talk in the GERAD seminar at Polytechnique Montreal about some work on learning dynamics in games.