Artificial Intelligence

SIFT has gathered extensive experience in multiple areas in the field of artificial intelligence. Automatic intent recognition, also referred to as plan recognition, is a critical challenge for intelligent user interfaces (to determine what a user is trying to do, and how the UI can offer help), computer security (to determine the objectives of an attacker), sketch understanding, natural language understanding, and other contemporary problems. SIFT researchers pioneered the use of Bayesian probabilistic methods in intent recognition. In cooperation with University researchers, SIFT has developed the Yappr system for intent recognition that achieves new levels of computational efficiency by using sophisticated techniques based on parsing.

Another prominent research area for SIFT is Automated Planning. SIFT researchers have used hierarchical task network (HTN) planning to develop a shared human/automation task model in Playbook® systems. As part of this effort, SIFT has led the maintenance of the open source SHOP2 HTN planner, originally developed by Dana Nau's research group at the University of Maryland. SIFT researchers have applied HTN planning in many areas including planning for unmanned air vehicles (UAVs), automatically composing semantic web services into workflows, etc.

SIFT researchers have been active in the area where planning, control theory and automatic verification intersect. Our work on the CIRCA system involves automatically planning (synthesizing) control programs that provide hard real-time performance guarantees, allowing them to be used in mission-critical applications. The CIRCA technology also allows non real-time computation techniques (planning, search, optimization) to be interleaved with real-time computations in an integrated system. SIFT researchers have applied the CIRCA technology to work on both deterministic and stochastic systems, in areas including UAV control and satellite and cyber-defense.