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Improved free form evolution for angry birds structures

Published: 13 July 2019 Publication History

Abstract

This paper presents an original approach based on evolutionary algorithms for building structures that are stable under gravity for the physics-based puzzle game Angry Birds, with the ultimate objective of creating Angry Birds levels with the minimum number of constraints. We have created a custom open source evolutionary computation library that implement an evolutionary algorithm whose main challenges have been to design a fitness function that, first, avoids when possible the time-consuming actual execution of the game, and, then, takes into account the different ways in which a structure is not sound and eliminates them. In order to test the method six experiments have been carried out, obtaining a variety of stable structures, which is the first path for the generation of levels that are aesthetically pleasing as well as playable.

References

[1]
Laura Calle, {n. d.}. Angry Birds Level Generator Github repository, https://github.com/Laucalle/AngryBirdsLevelGenerator. ({n. d.}). Accessed: 2018-10-30.
[2]
Laura Calle, {n. d.}. Science Birds adaptation. https://github.com/Laucalle/Science-Birds, ({n. d.}). Accessed: 2019-04-17.
[3]
Laura Calle, Juan Julián Merelo Guervós, Antonio Mora García, and José Mario García Valdez. 2019. Free Form Evolution for Angry Birds Level Generation. In Applications of Evolutionary Computation - 22nd International Conference, EvoApplications 2019, Held as Part of EvoStar 2019, Leipzig, Germany, April 24--26, 2019, Proceedings (Lecture Notes in Computer Science), Paul Kaufmann and Pedro A. Castillo (Eds.), Vol. 11454. Springer, 125--140.
[4]
Erin Catto. 2011. Box2D: A 2D Physics engine for games. (2011).
[5]
Lucas Ferreira and Claudio Toledo. 2014. A search-based approach for generating angry birds levels. In Computational intelligence and games (cig), 2014 ieee conference on. IEEE, 1--8.
[6]
Matthew Stephenson and Jochen Renz. 2016. Procedural generation of complex stable structures for angry birds levels. In Computational Intelligence and Games (CIG), 2016 IEEE Conference on. IEEE, 1--8.

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  • (2020)Recent Research on AI in Games2020 International Wireless Communications and Mobile Computing (IWCMC)10.1109/IWCMC48107.2020.9148327(505-510)Online publication date: Jun-2020

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    cover image ACM Conferences
    GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion
    July 2019
    2161 pages
    ISBN:9781450367486
    DOI:10.1145/3319619
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Publication History

    Published: 13 July 2019

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    Author Tags

    1. angry birds
    2. evolutionary algorithm
    3. game development
    4. level generation
    5. search-based procedural content generator

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    • Research-article

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    • Ministerio de Economía y Competitividad

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    GECCO '19
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    GECCO '19: Genetic and Evolutionary Computation Conference
    July 13 - 17, 2019
    Prague, Czech Republic

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    Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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    • (2020)Recent Research on AI in Games2020 International Wireless Communications and Mobile Computing (IWCMC)10.1109/IWCMC48107.2020.9148327(505-510)Online publication date: Jun-2020

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