Max Olan Smith

I am a core team researcher at H where we're developing strategic foundation models.

I received my Ph.D. from the University of Michigan, where I was advised by Michael P. Wellman. I have also had the pleasure of working with the Game Theory team at DeepMind, Paris and at the Montréal Institute for Learning Algorithms with Aaron Courville.

Email  /  CV  /  Google Scholar

Co-Learning Empirical Games and World Models
Max Olan Smith, Michael P. Wellman
1st Reinforcement Learning Conference, 2024.
[pdf] [arxiv]
Strategic Knowledge Transfer
Max Olan Smith, Thomas Anthony, Michael P. Wellman
Journal of Machine Learning Research (JMLR), 2023.
[pdf] [html] [poster]
Population-based Evaluation in Repeated Rock-Paper-Scissors as a Benchmark for Multiagent Reinforcement Learning
Marc Lanctot, John Schultz, Neil Burch, Max Olan Smith, Daniel Hennes, Thomas Anthony, Julien Perolat
Transactions of Machine Learning Research, 2023.
[pdf] [arXiv]
Learning to Play Against Any Mixture of Opponents
Max Olan Smith, Thomas Anthony, Michael P. Wellman
Frontiers in AI, 2023. (Originally appeared on arXiv in 2020).
Iterative Empirical Game Solving via Single Policy Best Response
Max Olan Smith, Thomas Anthony, Michael P. Wellman
International Conference on Learning Representations (ICLR), 2021. (Spotlight).
[pdf] [poster] [slides]
No Press Diplomacy: Modeling Multi-Agent Gameplay
Philip Paquette, Yuchen Lu, Steven Bocco, Max Olan Smith, Satya Ortiz-Gagne, Jonathan K. Kummerfeld, Satinder Singh, Joelle Pineau, Aaron Courville.
Advances in Neural Information Processing Systems (NeurIPS), 2019.
[pdf] [poster] [code]
Speaker Naming in Movies
Mahmoud Azab, Mingzhe Wang, Max Olan Smith, Moriyuki Kojima, Jia Deng, and Rada Mihalcea.
North American Chapter of the Association for Computational Linguistics (NAACL), 2018.
Long Term Effects of Pair Programming
Max Olan Smith, Andrew Giugliano, and Andrew DeOrio.
IEEE Transactions on Education, 2017.
[pdf] [slides]
A Unified Framework for Automatic Wound Segmentation and Analysis with Deep Convolutional Neural Networks
Changhan Wang, Xinchen Yan, Max Olan Smith, Kanika Kochhar, Marcie Rubin, Stephen M. Warren, James Wrobel, and Honglak Lee.
IEEE Engineering in Medicine and Biology (EMBC), 2015.