---
title: "Fast Planning with Iterative Macros"
authors:
  - "Adi Botea"
  - "Martin Müller"
  - "Jonathan Schaeffer"
doi: ""
url: "https://ijcai.org/proceedings/2007/295"
pdf: "https://ijcai.org/proceedings/2007/0295.pdf"
venue: "Proceedings of the Twentieth International Joint Conference on Artificial Intelligence"
year: 2007
pages: "1828-1832"
track: ""
keywords:
---

# Fast Planning with Iterative Macros

Adi Botea, Martin Müller, Jonathan Schaeffer

*Proceedings of the Twentieth International Joint Conference on Artificial Intelligence*, pages 1828-1832.

## Abstract

Research on macro-operators has a long history in planning and other search applications. There has been a revival of interest in this topic, leading to systems that successfully combine macro-operators with current state-of-the-art planning approaches based on heuristic search. However, research is still necessary to make macros become a standard, widely-used enhancement of search algorithms. This article introduces sequences of macro-actions, called iterative macros. Iterative macros exhibit both the potential advantages (e.g., travel fast towards goal) and the potential limitations (e.g., utility problem) of classical macros, only on a much larger scale. A family of techniques are introduced to balance this trade-off in favor of faster planning. Experiments on a collection of planning benchmarks show that, when compared to low-level search and even to search with classical macro-operators, iterative macros can achieve an impressive speed-up in search.