Partial-Order, Partially-Seen Observations of Fluents or Actions for Plan Recognition as Planning

TL;DR

This paper extends plan recognition as planning to handle partial, partially-seen observations of actions and fluents, improving accuracy and efficiency in complex, real-world scenarios.

Contribution

It redefines observation types, provides a new compilation method accommodating these observations, and demonstrates improved accuracy and reduced solution size over previous approaches.

Findings

Our method is as accurate or more accurate than baseline.

It can significantly reduce the size of the goal set.

The approach is adaptable to other planning-based recognition techniques.

Abstract

This work aims to make plan recognition as planning more ready for real-world scenarios by adapting previous compilations to work with partial-order, half-seen observations of both fluents and actions. We first redefine what observations can be and what it means to satisfy each kind. We then provide a compilation from plan recognition problem to classical planning problem, similar to original work by Ramirez and Geffner, but accommodating these more complex observation types. This compilation can be adapted towards other planning-based plan recognition techniques. Lastly we evaluate this method against an "ignore complexity" strategy that uses the original method by Ramirez and Geffner. Our experimental results suggest that, while slower, our method is equally or more accurate than baseline methods; our technique sometimes significantly reduces the size of the solution to the plan recognition problem, i.e, the size of the optimal goal set. We discuss these findings in the context of plan recognition problem difficulty and present an avenue for future work.