A Series of Unlikely Events: Learning Patterns by Observing Sequential Behavior
• Poster
This poster represents research to apply Inverse Reinforcement Learning techniques to model sequential behavior.
Publisher
Software Engineering Institute
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.