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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2021
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2107.04635 |
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| _version_ | 1866909131552587776 |
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| author | Piotrowski, Wiktor Stern, Roni Klenk, Matthew Perez, Alexandre Mohan, Shiwali de Kleer, Johan Le, Jacob |
| author_facet | Piotrowski, Wiktor Stern, Roni Klenk, Matthew Perez, Alexandre Mohan, Shiwali de Kleer, Johan Le, Jacob |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2107_04635 |
| institution | arXiv |
| publishDate | 2021 |
| record_format | arxiv |
| spellingShingle | Playing Angry Birds with a Domain-Independent PDDL+ Planner Piotrowski, Wiktor Stern, Roni Klenk, Matthew Perez, Alexandre Mohan, Shiwali de Kleer, Johan Le, Jacob Artificial Intelligence 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. |
| title | Playing Angry Birds with a Domain-Independent PDDL+ Planner |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2107.04635 |