---
title: "Getting the Most Out of Pattern Databases for Classical Planning"
authors:
  - "Florian Pommerening"
  - "Gabriele Röger"
  - "Malte Helmert"
doi: ""
url: "https://ijcai.org/proceedings/2013/347"
pdf: "https://ijcai.org/proceedings/2013/0347.pdf"
venue: "Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence"
year: 2013
pages: "2357-2363"
track: ""
keywords:
---

# Getting the Most Out of Pattern Databases for Classical Planning

Florian Pommerening, Gabriele Röger, Malte Helmert

*Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence*, pages 2357-2363.

## Abstract

The iPDB procedure by Haslum et al. is the state-of-the-art method for computing additive abstraction heuristics for domain-independent planning. It performs a hill-climbing search in the space of pattern collections, combining information from multiple patterns in the so-called canonical heuristic. We show how stronger heuristic estimates can be obtained through linear programming. An experimental evaluation demonstrates the strength of the new technique on the IPC benchmark suite.