Robust and Scalable Multiagent Reinforcement Learning in
Adversarial Scenarios

Robust and Scalable Multiagent Reinforcement Learning in Adversarial Scenarios

Multiagent decision-making is a ubiquitous problem with many real-world applications, such as autonomous driving, multi-player video games, and robot team sports. Key challenges of multiagent learning include the presence of uncertainty in the other agent’s behaviors and the curse of dimensionality...

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Bibliographic Details
Main Author:	Shen, Macheng
Other Authors:	How, Jonathan P.
Format:	Thesis
Published:	Massachusetts Institute of Technology 2022
Online Access:	https://hdl.handle.net/1721.1/144626

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