---
title: "From Interaction Data to Plan Libraries: A Clustering Approach"
authors:
  - "Mathias Bauer"
doi: ""
url: "https://ijcai.org/proceedings/1999/137"
pdf: "https://ijcai.org/proceedings/1999/0137.pdf"
venue: "Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence"
year: 1999
pages: "962-966"
track: "Planning and Scheduling"
keywords:
---

# From Interaction Data to Plan Libraries: A Clustering Approach

Mathias Bauer

*Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence*, pages 962-966.

## Abstract

Plan libraries are the most important knowledge source of many plan recognition systems. The plan decom positions they contain provide information about how a plan has to be executed to actually achieve its associated goals and be recognized by the system. This paper presents an approach to the automatic acquisition of plan decompositions from sample action sequences. In parti cular a clustering algorithm is introduced that allows groups of "similar" sequen ce s to be discovered and used for the generat ion of plan libraries. Empirical tests indicate that these libraries can indeed be successfully used for plan recognition purposes.