Bora Yongacoglu – at NeurIPS 2024 in Vancouver!
I’m an applied mathematician and machine learning researcher based in Ontario, Canada. I’m currently on the industry job market and looking for new collaborations and projects.
My research interests are varied and interdisciplinary, but mostly revolve around multi-agent learning and game theory. These days, I am especially interested in adversarial machine learning and alignment.
Most recently, I was a postdoctoral fellow with the Department of Electrical and Computer Engineering at the University of Toronto. Prior to that, I received my PhD in Mathematics from Queen’s University.
Research Interests:
- learning in games
- multi-agent reinforcement learning
- mean-field games
For a complete list of papers and preprints, please check out my publications page.
Contact:
If you’re interested in collaborating or if you have any questions/comments you’d like to share, you can reach me by email at bora.yongacoglu (at) utoronto.ca
News:
- (October 2024) Our paper “Independent Learning in Mean-Field Games: Satisficing Paths and Convergence to Subjective Equilibria” was accepted for publication in the Journal of Machine Learning Research. Stay tuned for updates!
- (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.