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

Playing Angry Birds with a Domain-Independent PDDL+ Planner