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A Series of Unlikely Events: Learning Patterns by Observing Sequential Behavior

October 2019 Poster
Eric Heim

This poster represents research to apply Inverse Reinforcement Learning techniques to model sequential behavior.

Abstract

Modeling patterns of behavior is a task that underlies numerous difficult artificial intelligence tasks: How do I detect when adversaries are deviating from normal routines? How can I automate the teaching of novice analysts to perform complex tasks as if they were expert analysts? In this work, we use a class of techniques called Inverse Reinforcement Learning (IRL) to model sequential behavior to answer questions like these and others.