# Playing Angry Birds with a Domain-Independent PDDL+ Planner

arXiv: https://arxiv.org/abs/2107.04635 · HTML: https://mlsanity.com/paper/2107.04635/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 7 references that are in the map.
- First posted on arXiv 9 Jul 2021.

## Built on by (most cited first, 1 of 1)

- [Real-World Planning with PDDL+ and Beyond](https://mlsanity.com/paper/2402.11901/) (2024)

## Abstract (arXiv)

This demo paper presents the first system for playing the popular Angry Birds game using a domain-independent planner. Our system models Angry Birds levels using PDDL+, a planning language for mixed discrete/continuous domains. It uses a domain-independent PDDL+ planner to generate plans and executes them. In this demo paper, we present the system's PDDL+ model for this domain, identify key design decisions that reduce the problem complexity, and compare the performance of our system to model-specific methods for this domain. The results show that our system's performance is on par with other domain-specific systems for Angry Birds, suggesting the applicability of domain-independent planning to this benchmark AI challenge.