Andrew Perrault

My research focuses on multi-agent interactions that arise in combating societal challenges, especially in the areas of conservation and public health. These interactions often involve challenges of uncertainty in the environment and the utility functions of the agents, necessitating approaches that handle scarce data. To achieve this end, I combine methodologies from game theory and multi-agent systems with machine learning, robust planning and optimization techniques.

I am an assistant professor in the Department of Computer Science and Engineering at The Ohio State University. This semester, I’m leading a seminar on reinforcement learning for optimization.

Before that, I was a Postdoctoral Fellow with Milind Tambe at Teamcore at the Center for Research on Computation and Society at Harvard. I completed my PhD in September 2018 under the supervision of Craig Boutilier at University of Toronto.

Research interests: decision-making in uncertain multi-agent systems with social good applications (game theory, sequential decision-making, machine learning, optimization, agent-based modeling)

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