A probabilistic plan recognition algorithm based on plan tree grammars

We present the PHATT algorithm for plan recognition. Unlike previous approaches to plan recognition, PHATT is based on a model of plan execution. We show that this clarifies several difficult issues in plan recognition including the execution of multiple interleaved root goals, partially ordered plans, and failing to observe actions. We present the PHATT algorithm's theoretical basis, and an implementation based on tree structures. We also investigate the algorithm's complexity, both analytically and empirically. Finally, we present PHATT's integrated constraint reasoning for parametrized actions and temporal constraints.

Authors

• Christopher W. Geib
• Robert P. Goldman David J. Musliner

Keywords

• Plan recognition
• Bayesian methods
• Probabilistic grammars
• Task tracking
• Intent inference
• Goal recognition
• Action grammars