---
title: "Abstraction Heuristics for Classical Planning Tasks with Conditional Effects"
authors:
  - "Martín Pozo"
  - "Jendrik Seipp"
doi: "10.24963/ijcai.2025/957"
url: "https://ijcai.org/proceedings/2025/957"
pdf: "https://ijcai.org/proceedings/2025/0957.pdf"
venue: "Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence"
year: 2025
pages: "8608-8616"
track: "Main Track"
keywords:
  - "Planning and Scheduling: PS: Search in planning and scheduling"
---

# Abstraction Heuristics for Classical Planning Tasks with Conditional Effects

Martín Pozo, Jendrik Seipp

*Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence*, pages 8608-8616. DOI: [10.24963/ijcai.2025/957](https://doi.org/10.24963/ijcai.2025/957)

## Abstract

In planning tasks, conditional effects model action outcomes that depend on the current state of the world. Conditional effects are a crucial modeling feature since compiling them away can cause an exponential growth in task size. However, only a few admissible heuristics support them. To add abstraction heuristics to this set, we show how to compute projections, Cartesian abstractions and merge-and-shrink abstractions for tasks with conditional effects. Our experiments show that these heuristics are competitive with, and often surpass, the state-of-the-art for conditional-effect tasks.