Creating a hyper-agent for solving angry birds levels

Matthew Stephenson, Jochen Renz

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    13 Citations (Scopus)

    Abstract

    Over the past few years the Angry Birds AI competition has been held in an attempt to develop intelligent agents that can successfully and efficiently solve levels for the video game Angry Birds. Many different agents and strategies have been developed to solve the complex and challenging physical reasoning problems associated with such a game. However, the performance of these various agents is non-transitive and varies significantly across different levels. No single agent dominates all situations presented, indicating that different procedures are better at solving certain levels than others. We therefore propose the construction of a hyper-agent that selects from a portfolio of sub-agents whichever it believes is best at solving any given level. This hyper-agent utilises key features that can be observed about a level to rank the available candidate algorithms based on their expected score. The proposed method exhibits a significant increase in performance over the individual sub-agents, and demonstrates the potential of using such an approach to solve other physics-based games or problems.

    Original languageEnglish
    Title of host publicationProceedings of the 13th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2017
    PublisherAAAI Press
    Pages234-240
    Number of pages7
    ISBN (Electronic)9781577357919
    Publication statusPublished - 2017
    Event13th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2017 - Snowbird, Little Cottonwood Canyon, United States
    Duration: 5 Oct 20179 Oct 2017

    Publication series

    NameProceedings of the 13th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2017

    Conference

    Conference13th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2017
    Country/TerritoryUnited States
    CitySnowbird, Little Cottonwood Canyon
    Period5/10/179/10/17

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