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

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