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.
@article{arxiv.2107.04635,
title = {Playing Angry Birds with a Domain-Independent PDDL+ Planner},
author = {Wiktor Piotrowski and Roni Stern and Matthew Klenk and Alexandre Perez and Shiwali Mohan and Johan de Kleer and Jacob Le},
journal= {arXiv preprint arXiv:2107.04635},
year = {2024}
}
Comments
2 pages, submitted to ICAPS 2021 Demonstration Track