Supporting Interleaved Plans in Learning Hierarchical Plan Libraries for Plan Recognition.
Martín G. Marchetta, R. Forraldellas · INTELIGENCIA ARTIFICIAL · 2006
"Most of the available plan recognition techniques are based on the use of a plan library in order to inferusers intentions and/or strategies. Until some years ago, plan libraries were completely hand coded byhuman experts, which is an expensive, error prone and slow process. Besides, plan recognition systems withhand-coded plan libraries are not easily portable to new domains, and the creation of plan libraries requirenot only a domain expert, but also a knowledge representation expert. These are the main reasons whythe problem of automatic generation of plan libraries for plan recognition, has gained much importance inrecent years. Even when there is considerable work related to the plan recognition process itself, less workhas been done on the generation of such plan libraries. In this paper, we present an algorithm for learninghierarchical plan libraries from action sequences, based on a few simple assumptions and with little givendomain knowledge, and we provide a novel mechanism for supporting interleaved plans in the input examplecases."