University of Texas

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Visible to the public Safety-Constrained Reinforcement Learning for MDPs

ABSTRACT
Many formal system models are inherently stochastic, consider for instance randomized distributed algorithms (where randomization breaks the symmetry between processes), security (e.g., key generation at encryption), systems biology (where species randomly react depending on their concentration), or embedded systems (interacting with unknown and varying environments).

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Visible to the public Cyber Trust and Suspicion

Eunice Santos works in the areas of large-scale distributed processing, computational modeling, complex adaptive systems, and human modeling with applications to the biological, physical, and social sciences. She is the Founding Director of the Institute of Defense & Security. She also served as Chair of Computer Science. She joined the University of Texas at El Paso in 2009 after serving as a Senior Research Fellow at the US Department of Defense's Center for Technology and National Security Policy.