A Series of Unlikely Events: Learning Patterns by Observing Sequential Behavior (video)
• Video
Watch SEI principal investigator Eric Heim discuss research to develop novel Inverse Reinforcement Learning (IRL) techniques as efficient and effective means for DoD/IC to perform activity-based intelligence or to teach novices how to perform tasks.
Publisher
Software Engineering Institute
Watch
Abstract
The Department of Defense (DoD) and the intelligence community (IC) frequently analyze activity based intelligence (ABI) to inform missions about routine patterns of life (POL) and unlikely events that signal important changes. We propose an alternative approach, inverse reinforcement learning
(IRL), that observes all states and actions in data and computes a statistical model of the world that includes whether each behavior is part of a routine.