Pitako - Recommending game design elements in Cicero

Tiago Machado, Dan Gopstein, Andy Nealen, Julian Togelius

    Research output: Chapter in Book/Report/Conference proceedingConference contribution


    Recommender Systems are widely and successfully applied in e-commerce. Could they be used for designƒ In this paper, we introduce Pitako1, a tool that applies the Recommender System concept to assist humans in creative tasks. More specifically, Pitako provides suggestions by taking games designed by humans as inputs, and recommends mechanics and dynamics as outputs. Pitako is implemented as a new system within the mixed-initiative AI-based Game Design Assistant, Cicero. This paper discusses the motivation behind the implementation of Pitako as well as its technical details and presents usage examples. We believe that Pitako can influence the use of recommender systems to help humans in their daily tasks.

    Original languageEnglish (US)
    Title of host publicationIEEE Conference on Games 2019, CoG 2019
    PublisherIEEE Computer Society
    ISBN (Electronic)9781728118840
    StatePublished - Aug 2019
    Event2019 IEEE Conference on Games, CoG 2019 - London, United Kingdom
    Duration: Aug 20 2019Aug 23 2019

    Publication series

    NameIEEE Conference on Computatonal Intelligence and Games, CIG
    ISSN (Print)2325-4270
    ISSN (Electronic)2325-4289


    Conference2019 IEEE Conference on Games, CoG 2019
    Country/TerritoryUnited Kingdom


    • AI-Game Design Assistant
    • Exploratory design
    • Frequent Itemset Data Mining
    • Recommender Systems

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Graphics and Computer-Aided Design
    • Computer Vision and Pattern Recognition
    • Human-Computer Interaction
    • Software


    Dive into the research topics of 'Pitako - Recommending game design elements in Cicero'. Together they form a unique fingerprint.

    Cite this