The FF Planning System: Fast Plan Generation Through Heuristic Search

TL;DR

The FF planning system introduces a novel heuristic search method combining hill-climbing with systematic search, significantly improving plan generation speed and efficiency in automated planning tasks.

Contribution

It presents a new heuristic search strategy that enhances plan generation speed without assuming fact independence, outperforming previous systems like HSP.

Findings

FF was the top performer at AIPS-2000 planning competition.

The new heuristic reduces search space effectively.

FF demonstrates superior runtime performance over HSP.

Abstract

We describe and evaluate the algorithmic techniques that are used in the FF planning system. Like the HSP system, FF relies on forward state space search, using a heuristic that estimates goal distances by ignoring delete lists. Unlike HSP's heuristic, our method does not assume facts to be independent. We introduce a novel search strategy that combines hill-climbing with systematic search, and we show how other powerful heuristic information can be extracted and used to prune the search space. FF was the most successful automatic planner at the recent AIPS-2000 planning competition. We review the results of the competition, give data for other benchmark domains, and investigate the reasons for the runtime performance of FF compared to HSP.