The Computational Complexity of Angry Birds (Extended Abstract)

Matthew Stephenson; Jochen Renz; Xiaoyu Ge

doi:10.24963/IJCAI.2020/716

The Computational Complexity of Angry Birds (Extended Abstract)

Matthew Stephenson, Jochen Renz, Xiaoyu Ge

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceeding › Academic › peer-review

Abstract

In this paper we present several proofs for the computational complexity of the physics-based video game Angry Birds. We are able to demonstrate that solving levels for different versions of Angry Birds is either NP-hard, PSPACE-hard, PSPACE-complete or EXPTIME-hard, depending on the maximum number of birds available and whether the game engine is deterministic or stochastic. We believe that this is the first time that a single-player video game has been proven EXPTIME-hard.

Original language	English
Title of host publication	Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI-20)
Pages	5105-5109
DOIs	https://doi.org/10.24963/IJCAI.2020/716
Publication status	Published - Jul 2020
Event	29yh International Joint Conference on Artificial Intelligence - Online, Yokohama, Japan Duration: 7 Jan 2021 → 15 Jan 2021 Conference number: 29 https://ijcai20.org/

Conference

Conference	29yh International Joint Conference on Artificial Intelligence
Abbreviated title	IJCAI 2020
Country/Territory	Japan
City	Yokohama
Period	7/01/21 → 15/01/21
Internet address	https://ijcai20.org/

Access to Document

10.24963/IJCAI.2020/716

Cite this

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title = "The Computational Complexity of Angry Birds (Extended Abstract)",

abstract = "In this paper we present several proofs for the computational complexity of the physics-based video game Angry Birds. We are able to demonstrate that solving levels for different versions of Angry Birds is either NP-hard, PSPACE-hard, PSPACE-complete or EXPTIME-hard, depending on the maximum number of birds available and whether the game engine is deterministic or stochastic. We believe that this is the first time that a single-player video game has been proven EXPTIME-hard.",

author = "Matthew Stephenson and Jochen Renz and Xiaoyu Ge",

note = "DBLP's bibliographic metadata records provided through http://dblp.org/search/publ/api are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.; 29yh International Joint Conference on Artificial Intelligence <br/>, IJCAI 2020 ; Conference date: 07-01-2021 Through 15-01-2021",

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doi = "10.24963/IJCAI.2020/716",

language = "English",

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booktitle = "Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI-20)",

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AU - Renz, Jochen

AU - Ge, Xiaoyu

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N2 - In this paper we present several proofs for the computational complexity of the physics-based video game Angry Birds. We are able to demonstrate that solving levels for different versions of Angry Birds is either NP-hard, PSPACE-hard, PSPACE-complete or EXPTIME-hard, depending on the maximum number of birds available and whether the game engine is deterministic or stochastic. We believe that this is the first time that a single-player video game has been proven EXPTIME-hard.

AB - In this paper we present several proofs for the computational complexity of the physics-based video game Angry Birds. We are able to demonstrate that solving levels for different versions of Angry Birds is either NP-hard, PSPACE-hard, PSPACE-complete or EXPTIME-hard, depending on the maximum number of birds available and whether the game engine is deterministic or stochastic. We believe that this is the first time that a single-player video game has been proven EXPTIME-hard.

U2 - 10.24963/IJCAI.2020/716

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M3 - Conference article in proceeding

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EP - 5109

BT - Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI-20)

T2 - 29yh International Joint Conference on Artificial Intelligence <br/>

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